title_s
stringlengths 2
79
| title_dl
stringlengths 0
200
| source_url
stringlengths 13
64
| authors
listlengths 0
10
| snippet_s
stringlengths 0
291
| text
stringlengths 21
100k
| date
timestamp[ns]date 1926-02-14 00:00:00
2030-07-14 00:00:00
| publish_date_dl
stringlengths 0
10
| url
stringlengths 15
590
| matches
listlengths 1
278
|
|---|---|---|---|---|---|---|---|---|---|
Will ChatGPT take my job? Experts reveal the five ...
|
Will ChatGPT take my job? Experts reveal the five professions at most risk from AI
|
https://www.dailymail.co.uk
|
[
"Rob Waugh",
"Rob Waugh For Dailymail.Com"
] |
Artificial intelligence will lead to 'serious job losses' across the retail sector, Saidi believes. 'As we've seen, checkout staff, customer service assistants ...
|
AI chatbot ChatGPT has sparked fears that artificial intelligence could automate millions of jobs out of existence.
Zak Saidi, creative director and AI Lead of creative agency IZSRI, which already uses AI to automate some writing tasks, says that the impact of AI will be felt across many sectors within the next three years.
He said he already uses ChatGPT to draft written content and other AI tools for attention marketing and detecting social media trends.
ChatGPT has hit 100 million users just two months after launch - by comparison, it took TikTok nine months to reach the milestone - and secured a $10 billion investment from Microsoft.
So which jobs are most likely to be replaced by 'generative AI'? And how soon could it happen?
Copywriters and bloggers
Copywriters and bloggers could soon be out of work because of AI tools such as ChatGPT - but an expert says the most talented human writers will remain sought after (file photo)
Copywriters, bloggers and people who produce online copy could be among the first to fall in the AI revolution, Saidi believes.
He says, 'We work with a lot of copywriters and there is certainly a lot of industry talk around the replacement of content writers by AI technology.
'ChatGPT is free, copywriters aren't – we expect more tech-savvy small businesses to turn to ChatGPT and its AI counterparts when generating more content.'
Buzzfeed announced earlier this year that it would use ChatGPT to generate some online content.
Tech site CNET faced controversy last month after it was revealed that the site had used AI to generate articles. Some of these articles were then found to be riddled with errors.
AI-powered content creation platform Jasper says tens of thousands of clients have already used its software to create adverts, blogs and marketing emails.
But the future isn't quite as bleak for highly skilled copywriters, Saidi said.
'Nothing, we believe, can replace human creativity. In its current form ChatGPT generates highly generic content,' he explained.
'But it's still a huge concern for some copywriters that as this tech develops in its sophistication that at a certain point a lot of businesses will turn to AI to provide their content writing services.'
Retail staff
Artificial intelligence will lead to 'serious job losses' across the retail sector, Saidi believes.
'As we've seen, checkout staff, customer service assistants and personal shoppers are slowly being replaced by AI bots – powered by the exact same kind of artificial learning technology that ChatGPT works off,' he said.
Artificial intelligence company Standard AI acquired self-checkout company Skip this year with a goal to create 'autonomous retail', to 'give retailers immediate relief from their labor challenges', the company said.
Saidi says, 'In some ways, it can be said that AI works to free workers from the more menial tasks, giving them the time to take on more managerial and creative roles.
'But we have to consider that there are only so many managers that can manage retail stores!'
Software engineers and cybersecurity experts
As well as producing convincing text in English, ChatGPT can also write computer code in languages such as Python.
Demonstrations shown off by OpenAI show ChatGPT debugging code in response to prompts.
ChatGPT maker OpenAI also makes a different version, Codex, specifically for writing computer code, which Microsoft uses in its GitHub Copilot.
Saidi says that such technology could have an immediate and wide-ranging impact on developers - and even cybersecurity experts.
'Now, this is where we can start to get a bit concerned, even with applications like ChatGPT still in their rudimentary form,' he continued.
'ChatGPT generates lines of html code without having to think, solving complex errors in sequence of code infinitely faster than a human.
'This, to a certain extent, is throwing the role of supporting software engineers into question.
'Whilst you still do need a human to plan out a software development project, ChatGPT can act as a crucial tool to resolve broken code and build basic applications – a role that would have been previously reserved for junior software engineers.'
OpenAI is currently hiring hundreds of developers to 'train' the AI to improve its coding abilities.
Cybercriminals are already boasting of using tools such as ChatGPT to automate everything from writing malware to creating dark web markets - and Saidi says that AI tools could impact cybersecurity professionals' jobs.
Graphic designers and visual artists
Graphic designers could be replaced with AI tools as well, with tools such as Dall-E creating around 2million new images every day (file photo)
Graphic art tools such as Dall-E, Stable Diffusion and Midjourney could impact the livelihoods of designers, illustrators and visual artists, Saidi says.
Dall-E (also operated by OpenAI) generates 2million images per day, the company announced last year.
Midjourney sparked controversy when it won an art competition at the Colorado State Fair.
Stock image giant Getty Images launched legal proceedings against Stability AI, maker of Stable Diffusion, alleging that it has copied millions of its images.
Saidi says that the ability to produce images cheaply and rapidly will make such technology very tempting for small businesses without the budget to pay for graphic designers, artists or illustrators.
Saidi says, 'It certainly puts the role of graphic designers and illustrators into question. Like ChatGPT, the imagery can be generic and tricky to refine, but with some work and optimization you can whip up some stunning visuals.
'Many still believe, and rightly so, that human creativity will always be at the core of design, with some creatives looking to AI for artistic inspiration, rather than a replacement for their assistant.'
More roles in tech?
As this technology displaces current roles in retail and marketing, Saidi believes it will create new roles in tech companies.
He says, 'We anticipate, and are witnessing the very genesis of, a huge recruitment drive in the tech industry, likely picking up a lot of retail and admin staff that have been displaced by the introduction of AI.'
| 2023-02-05T00:00:00 |
2023/02/05
|
https://www.dailymail.co.uk/health/us-health-weekend-features-project/article-11710217/Will-ChatGPT-job-Experts-reveal-five-professions-risk-AI.html
|
[
{
"date": "2023/02/05",
"position": 28,
"query": "AI job losses"
}
] |
Implementing AI in the Workplace for Business Growth
|
Implementing AI in the Workplace for Business Growth
|
https://move2ai.com
|
[] |
The success of AI adoption depends on several factors, such as having a clear strategy, sufficient data to train models, and the right infrastructure and talent ...
|
The start of 2023 seemed like the birth of Artificial Intelligence (AI) going mainstream and becoming an increasingly important tool for companies to stay ahead of the competition and achieve business growth. With the introduction of hundreds of applications that came on to the market it was obvious to many people that AI offered a range of benefits that can help companies to improve efficiency, boost productivity, and make better decisions. From automating routine tasks to providing data-driven insights.
Its important to realise that AI is much more then Chat GPT. You only have to look at the investment big tech players such as Microsoft and Google are making in the space.
In this article, we will dive in to some of the key benefits that companies can reap from implementing AI in the workplace for business growth.
Using AI to increase efficiency and productivity
One of the primary benefits of implementing AI in the workplace is increased efficiency and productivity. AI-powered technologies such as chatbots, virtual assistants, and machine learning algorithms can automate routine tasks and help employees to work more efficiently. For example, chatbots can be trained on your company information to answer questions specific to your company, freeing up employees to focus on more complex tasks. Virtual assistants can help employees to manage their schedules and reminders, allowing them to be more productive and efficient.
Improved decision making via analytics and data driven insights
Another key benefit of implementing AI in the workplace is improved decision making. AI-powered technologies can provide data-driven insights and recommendations that can help your company make better decisions. For example, machine learning algorithms can analyse large amounts of data to identify patterns and trends that can be used to inform business strategies especially with growing and scaling your e-Commerce business. This can help companies to make more informed decisions and stay ahead of the competition.
Having data is just the beginning, you need analytics and automation to really bring it to life.
Giving you more scope for growth
The success of AI adoption depends on several factors, such as having a clear strategy, sufficient data to train models, and the right infrastructure and talent in place. As the technology evolves, you need to ask if you want your company to be ahead of the competition. At Move2AI, we focus on helping you through the journey of empowering you use AI to grow and scale your company in the direction you wait.
The cost savings artificial intelligence offers to companies
One of the requests we often get asked is how can I bring services in-house and train my team to run tasks that we depend on agencies to do. In August 2022, we helped a property investment company to decrease advertising spend on paid media while increasing leads by 259%. By automating routine tasks, AI technologies can help companies to reduce labor costs and increase efficiency. Additionally, AI can help companies to make more informed decisions, reducing the risk of costly mistakes. A good example of this is looking at trends and customer sentiment in order to plan ad spend going forward.
Improved accuracy and consistency
Implementing AI in the workplace can help companies to improve accuracy and consistency. AI-powered technologies can provide data-driven insights and recommendations, helping companies to make better decisions. Additionally, AI technologies can automate routine tasks, reducing the risk of human error and ensuring consistent results.
Empowering your workforce to embrace artificial intelligence
AI is increasingly becoming a vital part of our daily lives both personal and working, so it is important for employees to be equipped with the skills to effectively adopt and work alongside it. The ability to work with AI is quickly becoming a critical skill set for all employees, regardless of their job title or industry. As a result, many organisations regardless of size are investing in training programs to help their employees develop the skills need to work with AI.
Developing a successful AI training program is to clearly define the training objectives.
What problem do you need to solve within your company?
What skills do employees need to develop in order to effectively use AI to tackle that problem?
What are the specific tasks and responsibilities that they will be required to perform?
Some of the most effective methods we use at Move2AI include hands-on workshops, one on one online training, team based online training courses, and mentoring programs. This is all backed up with our support packages that further help employees feel that they are being supported and developed. This, in turn, can improve overall job satisfaction, help employees to not feel threatened by AI and boost overall productivity.
| 2023-02-05T00:00:00 |
2023/02/05
|
https://move2ai.com/implementing-ai-in-the-workplace-for-business-growth/
|
[
{
"date": "2023/02/05",
"position": 5,
"query": "workplace AI adoption"
}
] |
AI in Safety Data Sheet (SDS) Authoring Tools for Chemical
|
AI in Safety Data Sheet (SDS) Authoring Tools for Chemical
|
https://cloudsds.com
|
[] |
AI, or artificial intelligence, is continuing to grow in influence and adoption. In the workplace, this means that new digital solutions are being created.
|
AI in Safety Data Sheet (SDS) Authoring Tools for Chemical Manufacturers
AI, or artificial intelligence, is continuing to grow in influence and adoption. In the workplace, this means that new digital solutions are being created to streamline processes. AI-driven software like natural language processing (NLP) is making it possible for computers to understand human speech, learn from information input by humans, and make decisions based on that information. The use of AI in chemistry has also advanced significantly over the past few years. From virtual laboratory assistants with AI capabilities to AI-assisted analytics tools for chemists, developers have made it easier than ever for chemical manufacturers to implement AI in their workflows and processes. There are many ways that companies can leverage artificial intelligence technologies to create safer products and materials at a faster rate. Here’s how you can use AI in SDS authoring tools for chemical manufacturers…
AI-Assisted Data Research and Discovery
AI has the potential to significantly streamline and speed up data research and discovery. NLP-driven AI software will not only be able to understand human speech, but also learn from the information being inputed. AI will also be able to make decisions based on that information, allowing it to become a virtual lab assistant for chemists and scientists. With this assistance, researchers will be able to focus on the creative side of their work. They’ll be able to spend less time on the process of researching chemicals and more time on the creative process. This can help improve the quality of research, making it more accurate and reliable. AI-assisted data research and discovery can be applied to a number of aspects of the chemical manufacturing process. AI can help marketers create new product ideas and discover new potential customers. It can also help scientists and engineers understand the potential of a given chemical. This can help them determine if they can use a certain chemical in their project or product. AI can even help sales and marketing teams better understand their customers and what they want. This can help them create more effective marketing campaigns and a better customer experience.
AI-Assisted Chemical Identification
Identifying chemicals is one of the most important aspects of chemical manufacturing. Whether you’re creating a new product or just need to know the exact compound and percentage of a substance in a reaction, this information is crucial. However, identifying chemicals can be difficult and time-consuming. AI can make chemical identification easier by using NLP. This allows AI to understand human speech, input, and language. It can then use that information to make decisions, just like a human would. AI can also use machine learning algorithms to constantly learn and improve its identification accuracy over time. This can make it easier for scientists to identify chemicals and accurately discover their percentage. AI can also be used to identify chemicals in the workplace. With AI-assisted identification software, workers will be able to input data about the chemicals they’re working with and the quantities they’ve been given. This information can then be used to help workers understand the risks associated with their job, what they’re working with, and the best practices for handling their chemicals. This can help reduce risk and create a safer work environment.
AI-Assisted Material Selection
AI can help scientists and engineers select the right materials for a given project. This can make it easier to find compatible materials and reduce the time it takes to complete a project. AI can understand the requirements of a project and the data that has been inputted by engineers. It can then use different machine learning algorithms to find compatible materials and chemicals that meet these requirements. It can also take into account any regulations or restrictions on the use of certain chemicals. This can help make sure you select the best materials for your project.
Human-AI Collaboration in SDS Authoring Tools for Chemical Manufacturers
One of the best ways to use AI in SDS authoring tools for chemical manufacturers is through human-AI collaboration. This allows humans and AI to work together to reach a shared goal and finish a task. This can be helpful in a number of different ways. For example, AI can take over the tedious tasks that humans don’t want to do or aren’t good at. This can help free up time for humans to spend on more important tasks. It can also help humans retain their creativity by allowing them to focus on the creative side of their work. AI can also help humans by providing them with information that they might not know or be able to find. This can help improve the quality of work being done and provide more accurate data for scientists and engineers. Although AI can be helpful, it’s important to remember that it also has its limitations. This means that AI will never be able to accurately replace humans. Instead, it can provide assistance and make tasks easier while also helping improve the overall quality of work.
Conclusion
Overall, AI has the potential to significantly improve the work done by chemical manufacturers. By leveraging AI-driven software, companies can make their work more accurate and efficient. They can also create a safer work environment by better understanding the chemicals they’re working with. With AI-driven software, SDS authoring tools for chemical manufacturers can improve their operations, create better products, and improve safety in the workplace.
| 2022-11-11T00:00:00 |
2022/11/11
|
https://cloudsds.com/blog/ai-in-safety-data-sheet-sds-authoring-tools-for-chemical-manufacturers/
|
[
{
"date": "2023/02/05",
"position": 46,
"query": "workplace AI adoption"
}
] |
The Work-From-Home Shock to Labor Markets, Fall 2023
|
The Work-From-Home Shock to Labor Markets, Fall 2023
|
https://www.nber.org
|
[
"Karen Glenn",
"Stephen Goss"
] |
Utilizing the Task Technology Fit model, the study assessed how well AI aligns with tasks of varying complexity and creativity. While the original focus was on ...
|
Scheme: 20 minutes for paper presentation followed by 10 each/discussant & general discussion (10-20 min)
Loading...
| 2023-02-05T00:00:00 |
https://www.nber.org/conferences/work-home-shock-labor-markets-fall-2023
|
[
{
"date": "2023/02/05",
"position": 43,
"query": "AI labor market trends"
},
{
"date": "2023/02/05",
"position": 78,
"query": "AI labor union"
}
] |
|
Universal basic income and A.I.
|
Universal basic income and A.I.
|
https://www.universalbasicincome.ai
|
[] |
We are a collaborative project dedicated to the study of artificial intelligence, human disintermediation and UBI or Universal Basic Income.
|
Minute 12:00 Above: A firm warning from Sam Altman, CEO of OpenAI.
"With stronger AI, we will have to think about how we share 'Wealth' in a very different way than we have in the past. The fundamental forces of capitalism and what makes it work break down.
Is it something like a Basic Income or a wealth redistribution? We are trying to study that, and it needs to be explored more.
People have yet to internalize what happens if the cultural playing field shifts this much.
So, they assume that a 'small tweak' on capitalism will work.
If you let yourself think 'science fiction dreamworld' out very far, where you can say - 'ok, AGI, start a new trillion-dollar company.'
And the AGI can be the CEO, it can figure out how to go raise capital, it can do all of the engineering, it can do the marketing, it can do the distribution, and you just typed in ONE command prompt and pushed "ENTER" - and the A.I. went off and did that.
That's weird. How do we live in a world like that?"
- Sam Altman, CEO of OpenAI
| 2023-02-05T00:00:00 |
https://www.universalbasicincome.ai/home
|
[
{
"date": "2023/02/05",
"position": 5,
"query": "universal basic income AI"
},
{
"date": "2023/03/01",
"position": 63,
"query": "universal basic income AI"
},
{
"date": "2023/05/01",
"position": 60,
"query": "universal basic income AI"
},
{
"date": "2023/06/01",
"position": 60,
"query": "universal basic income AI"
},
{
"date": "2023/08/01",
"position": 63,
"query": "universal basic income AI"
},
{
"date": "2023/10/01",
"position": 61,
"query": "universal basic income AI"
},
{
"date": "2024/03/01",
"position": 61,
"query": "universal basic income AI"
},
{
"date": "2024/06/01",
"position": 61,
"query": "universal basic income AI"
},
{
"date": "2024/08/01",
"position": 60,
"query": "universal basic income AI"
},
{
"date": "2024/11/01",
"position": 61,
"query": "universal basic income AI"
},
{
"date": "2024/12/01",
"position": 70,
"query": "universal basic income AI"
},
{
"date": "2025/01/01",
"position": 63,
"query": "universal basic income AI"
}
] |
|
ChatGPT: the future of AI to provide answers to employees?
|
Blog: ChatGPT: the future of AI to provide answers to employees?
|
https://www.pigro.ai
|
[] |
which affects knowledge sharing and usability. These are just some of the parameters used to understand any issues that impact the search for information in the ...
|
Chat GPT is an Artificial Intelligence capable of writing and generating content of all types and on any subject.
Nowadays it is talked about everywhere and this technology, which has been booming online since last November and within the first week of its launch has conquered one million users, has been described by many as revolutionary.
Yes, even we at Pigro have tried it, to test it in different fields and with different requests - we confess, some of the SEO titles of this article were generated by the chatbot! - and we tried to understand what daily tasks in the company could be simplified by its use.
And above all, what advantages and disadvantages it might have in the field of knowledge management and information retrieval.
In short, we think the potential is enormous, but... are we sure it can solve all our problems?
ChatGPT what is it and how to use it
How ChatGPT technology works
How GPT chatbot can speed up work in the company
Limitations and weaknesses of chatbot GPT
The future of AI to provide answers to users: human and artificial intelligence
ChatGPT what is it and how to use it
First of all, ChatGPT stands for “Chat Generative Pre-trained Transformer” and is an AI and machine learning-based chatbot created by OpenAI, a research and development company in the field of AI, in collaboration with Microsoft.
It is currently available online on the OpenAI website and you need to register with your email address to start using it.
Being a chat, to use it you need to write a request, insert a portion of text or an input phrase in the text bar, to start interacting. In addition to providing answers on topics of any category, the GPT chat is also able to write content, create lists, solve mathematical equations, translate languages, generate code, create summaries, provide instructions.
Below, a small recap of how this chatbot can be used:
Answer users' questions and also be used as a Customer Service chatbot. Write articles and blog posts on a large number of topics. Generate scripts and dialogues such as TV show scripts, video games, etc. Create product descriptions for a catalogue or e-commerce site, saving time and effort. Write social media captions with hashtags. Write poetry and song lyrics
How ChatGPT technology works
ChatGPT is based on a Deep-Learning model called Large Learning Model that leverages artificial intelligence and neural networks to store and learn from a large amount of data.
The chatbot was then trained on Open AI’s Instruct GPT or GPT-3.5 models, which are models where the pre-training phase has been optimised by human intervention.
In short, it suffices to know that thanks to all the training carried out on data, including manual pages and information on the Internet and programming languages, perfected with the help of human instructors, Chat GPT is able of understanding requests and provide answers, remembering previous interactions within the same conversation.
Here we asked the chatbot to explain the technology behind it:
Harnessing the Power of Pigro and ChatGPT for Seamless Knowledge Sharing in the Company
In today's fast-paced business environment, knowledge sharing is crucial for companies to stay competitive and innovative. With the advancements in AI and machine learning, tools like Pigro and ChatGPT are revolutionizing the way organizations manage and disseminate information within their workforce.
Pigro, a cutting-edge knowledge management system, provides companies with a comprehensive solution for organizing and accessing large amounts of documentation. It's intelligent algorithms and intuitive interface make it easy for employees to find the information they need quickly and accurately. By harnessing the power of Pigro, companies can streamline their knowledge-sharing processes and empower their employees to make informed decisions.
ChatGPT, on the other hand, takes knowledge sharing to a whole new level by leveraging the capabilities of AI and natural language processing. As mentioned earlier, this AI-powered chatbot developed by OpenAI and Microsoft can generate content, answer questions, and even provide instructions on a wide range of topics. By integrating ChatGPT into their workflow, companies can enhance their customer service, marketing, content creation, and HR processes.
Imagine a scenario where a salesperson needs to draft a business plan or an annual sales forecast. With the help of ChatGPT, they can simply provide the necessary data, and the chatbot will generate a comprehensive document in a matter of minutes. This not only saves time but also ensures consistency and accuracy in the generated content.
For marketers and content creators, ChatGPT can be a game-changer. It can assist in writing articles, product descriptions, social media copies, and even propose new content ideas. By collaborating with ChatGPT, marketers can boost their productivity and creativity, while also maintaining the quality and relevance of their content.
Customer care and help desk departments can also benefit from ChatGPT. The chatbot can automate the creation of FAQs and other user support content, freeing up valuable time for customer service representatives to focus on more complex issues. This not only improves customer satisfaction but also reduces costs for companies.
Lastly, HR departments can leverage ChatGPT to expedite the process of drafting company guidelines and policies. With its ability to understand requests and provide relevant answers, the chatbot can assist HR professionals in creating these documents more efficiently. This ensures that the company's policies are communicated clearly and consistently to all employees.
While Pigro and ChatGPT offer incredible benefits for seamless knowledge sharing in the company, it is important to acknowledge their limitations. As mentioned earlier, ChatGPT may not always provide the most accurate or up-to-date information, and its responses may be influenced by biases present in the training data. As such, human intervention and oversight are still necessary to ensure the quality and reliability of the content generated by these tools.
In conclusion, the power of Pigro and ChatGPT in facilitating seamless knowledge sharing in companies cannot be underestimated. By harnessing the capabilities of AI and machine learning, organizations can streamline their processes, increase productivity, and enhance decision-making. However, it is crucial to strike a balance between automation and human intervention to ensure the accuracy, relevance, and reliability of the information shared. With the continuous advancement of technology, it will be interesting to see how virtual assistants and knowledge management systems like Pigro evolve in the future to meet the ever-changing needs of businesses.
Limitations and weaknesses of chatbot GPT
It is clear now what the potential of this tool is but after testing it a little, or even just reading online, there are also some limitations that, as expected, chatGPT is proving to have.
Certainly, if you asked about very recent topics, you may have received a message in response indicating that the update of data available to the chatbot dates back to late 2021. It doesn’t know events that happened after that period.
Moreover, as explained by the developers, the AI behind ChatGPT is not immune from bias e prejudices, since it draws its answers from the base of information on which it has been trained.
Since the chatbot has been designed to be safe, harmless and avoid potentially damaging topics, it has by default intentional prejudices to prevent negative behaviour. So the answers provided may not be as neutral as you think, influenced by the "good intentions" for which it is set.
Obviously, it is still an artificial intelligence, therefore not able to make judgments, critical thinking, make decisions like the human brain and not even be creative.
And this can be a problem, as in the case of tech news website CNET, which from November until now has published around 70 article posts written by artificial intelligence, without communicating it transparently to readers.
This is according to Futurism, which identified the problem, noting a series of trivial mistakes in the content of the articles, as well as entire sentences that can be traced back to other articles previously published elsewhere, without any specific source citation. As a result, CNET first inserted correction notes in articles or notifications on the veracity of the content, then announced the suspension of the publication of AI-generated articles.
However, as some studies from Johns Hopkins University, New York University and Microsoft have argued, it should come as no surprise that there are phrases or excerpts from other content, because systems like Chat GPT that rely on LLM (Large Learning Models) exploit the vast amount of data entered for learning to generate new text, indeed "sometimes they copy substantially [...] from the training set" (source: Carola Frediani, Guerre di Rete, N.150 28 Jan 2023).
Content generated by AI needs, in fact, constant reworking to be original and not fall into plagiarism, as well as the fact that the more details are input into, the more GPT will be able to process a valid and less “mass-produced” response.
But, above all, the most criticised aspect is the accuracy and reliability of the answers. If the sources on which ChatGPT has been trained are currently not publicly available, transparency and truthfulness become a problem. In many cases some answers given by the system have proved false - not to say real fake news - presented as certain and therefore impossible to recognise if you know nothing about the subject.
Google is already taking advantage of the controversy by revealing that is developing a chatbot aimed to be a direct competitor of ChatGPT: Sparrow. Its strengths will be greater accuracy in answers and the ability to cite its sources, as well as being developed by Google, it will be able to count on frequent content updates and may be directly integrated into Google Search.
The future of AI to provide answers to users: human and artificial intelligence
GPT Chat is already so powerful and in the years to come will only perfect its operations, storing even more data and feedback. This means more simplicity in creating content, more automatically generated materials, but also more difficulty in ensuring quality and reliability.
So, at Pigro - which works with AI, we have produced chatbots, we have refined them and then fully dedicated our mission to knowledge management, providing precise and coherent answers to users, to minimize the effort of organizing and consulting large amounts of documentation - we cannot help but wonder:
So, what about virtual assistants that have been popular until now? What will be their function in the future?
Will information retrieval and knowledge management systems, like ours, still be useful to find information?
Will GPT Chat be the big competitor to beat? Will we be forced to evolve?
What does technological progress hold for us?
From these increasingly gripping and concrete doubts, a consideration sparked:
Despite the apparent ease with which chatGPT can be used to automate many tasks (such as in the basic requests of Customer Assistance, already carried out by chatbot) in order to engage in higher added value activities, the fact remains that to obtain a valid, up-to-date and reliable content, human intervention of improvement is still necessary.
Chat GPT is unable to reason, make value judgements, and provide source verification for information.
While representing a valuable ally with certainly remarkable abilities, the final step that gives validity to content must be provided to human intelligence.
So what can be our contribution?
Pigro has developed and is improving a feature to analyse content quality: Knowledge Insights measures the effectiveness of the company knowledge base and provides suggestions to increase it.
The knowledge base can be analysed, for example, in terms of content structure, or the presence of headings, paragraphs, redundant elements, broken links, etc. which affects the legibility and therefore the efficacy for the readers. Or can evaluate the repositories organization, the access permissions to folders, etc. which affects knowledge sharing and usability.
These are just some of the parameters used to understand any issues that impact the search for information in the companies. Each insight is provided with ad hoc suggestions to improve the efficiency of company documentation.
The Knowledge Insights tool from Pigro can be useful even when we have not directly produced the content, as in the case of those automatically generated by AI.
In conclusion, we believe that ChatGPT could be a disruptive technology to provide answers at an impressive speed, but in our opinion, the real potential of this tool lies in the ability to help people in the early stages of content creation, and cannot (nor should) replace human intervention.
In order not to witness in the future the flattening (also in terms of quality) of the contents in circulation are necessary, in fact, the elements of novelty and originality that only human thought can bring.
| 2023-02-05T00:00:00 |
https://www.pigro.ai/post/chatgpt-the-future-of-ai-to-provide-answers-to-employees
|
[
{
"date": "2023/02/05",
"position": 68,
"query": "ChatGPT employment impact"
}
] |
|
ResponseCX FAQ | AI Workers for Shopify Brands - Get Answers
|
Agentic AI for Shopify Brands
|
https://response.cx
|
[] |
Unlike chatbots that provide static responses, ResponseCX AI workers perform complex tasks such as order cancellations, subscription updates, and tailored ...
|
💬
Still have questions?
Our customer success team is here to help you get the most out of ResponseCX. Get personalized answers and see how AI workers can transform your business.
🚀 Most demos lead to implementation within 2 weeks
| 2023-02-05T00:00:00 |
https://response.cx/
|
[
{
"date": "2023/02/05",
"position": 53,
"query": "AI workers"
}
] |
|
XComms Ai | Streamline Your Internal Communications ...
|
Streamline Your Internal Communications and Improve Employee Engagement
|
https://www.xcomms.com
|
[] |
Enhance your internal communications and employee engagement with XComms AI Capabilities. Our AI-powered solution streamlines your communication processes ...
|
XComms is the ultimate solution for modern business communication needs. With a wide range of tools, XComms guarantees employee awareness and improves engagement levels across any organization.
With custom branding options to maintain a professional look and advanced AI technology to help create the most concise and engaging messaging, XComms is a game-changer in the world of business communication.
Modernize your communication strategy with XComms and unlock a new level of engagement and success.
| 2023-02-05T00:00:00 |
https://www.xcomms.com/ai-for-internal-communications-and-employee-engagement
|
[
{
"date": "2023/02/05",
"position": 73,
"query": "AI workers"
}
] |
|
The 14 best AI recruiting tools for hiring top talent in 2023
|
The 14 best AI recruiting tools for hiring top talent in 2023
|
https://superfounder.io
|
[] |
Here is our list of the best AI recruiting software for creating job descriptions, spotting relevant candidates, posting to job boards, high volume hiring and ...
|
AI recruiting software uses artificial intelligence and machine learning processes to help recruiters and hiring managers in their hiring process.
These applications can automate tasks like screening resumes, matching potentials, and scheduling interviews which can save time and optimize the recruitment process.
What is the best AI Recruiting software?
Well, it all depends on your specific needs, doesn't it? But here is our list of the best AI recruiting software for creating job descriptions, spotting relevant candidates, posting to job boards, high volume hiring and more.
🚀 Top 3 Picks for AI-Powered Recruitment Platforms:
Manatal - AI-powered recommendations, customizable interface, and extensive job board integration 🤖✨ BreezyHR - Comprehensive features, visual pipeline, and hassle-free candidate management 🌟🌬️ JobAdder - Intelligent skill matching, 200+ job boards, and excellent candidate experience 🔍💼
Manatal is hands down the top choice when it comes to AI-driven, all-in-one recruiting software. It's got everything you need, making it a breeze to use, and it's packed with cutting-edge tech. This platform is a game-changer for HR teams, recruitment agencies, and headhunters alike, thanks to its customizable and user-friendly interface.
Manatal AI recruiting software
What sets Manatal apart is its AI smarts that make candidate matching and profile enrichment a piece of cake. It's a must-have for anyone in the talent acquisition game. Plus, with its transparent pricing, top-notch support, and airtight security, it's no wonder people all over the world are singing its praises. In a nutshell, Manatal is the cream of the crop when it comes to recruitment software.
Manatal AI Screening of suitable candidates
Top 3 features and benefits:
AI-powered recommendations - Enhance candidate matching and profile enrichment, simplifying the hiring process.
- Enhance candidate matching and profile enrichment, simplifying the hiring process. Customizable, user-friendly interface - Easily adapt the platform to your recruitment workflow, making it accessible for all users.
- Easily adapt the platform to your recruitment workflow, making it accessible for all users. Extensive job board integration - Post jobs on 2,500+ free and premium channels, maximizing your reach to potential candidates.
What's good:
Transparent pricing - Flexible pricing plans with no hidden costs or lock-in contracts.
- Flexible pricing plans with no hidden costs or lock-in contracts. Exceptional support - Responsive 24/5 support via chat and video call for all your needs.
- Responsive 24/5 support via chat and video call for all your needs. High-security standards - SOC II Type 2 compliant, ensuring your data is secure and private.
What's not so good:
Limited to English and Spanish language - Currently, support and platform language is restricted to English and Spanish only.
Manatal AI Recruitment Platform Pricing
Pricing:
Offers a 14-day free trial and a range of plans including Professional ($15/user/month), Enterprise ($35/user/month), and Custom (on-demand pricing), catering to various business sizes and needs.
Breezys is not just a great all-in-one HR and recruiting solution, it's AI-powered Candidate Match Score can help you save time by quickly reviewing applications and identifying the top suitable candidates for your open roles. With this tool, your hiring team can instantly access a prioritized and unbiased list of the best-fit applicants. Don't waste any more time sifting through irrelevant applications - let Breezy do the heavy lifting for you!
Breezy HR
Top 3 features and benefits:
Drag-and-drop pipeline - Visualize and manage the entire recruitment process with ease, keeping track of candidates and making updates on-the-fly.
- Visualize and manage the entire recruitment process with ease, keeping track of candidates and making updates on-the-fly. Automation and collaboration tools - Streamline the hiring process with automated tasks, scheduling, and team collaboration features.
- Streamline the hiring process with automated tasks, scheduling, and team collaboration features. Broad job board integration - Access to 50+ free and premium job boards, increasing your reach to potential candidates.
BreezyHR Recruitment Pipeline
What's good:
Integration with existing tools - Seamless integration with popular HR tools like Slack, Google Calendar, and more.
- Seamless integration with popular HR tools like Slack, Google Calendar, and more. Candidate management - Comprehensive candidate management features, including candidate scoring and GDPR compliance.
- Comprehensive candidate management features, including candidate scoring and GDPR compliance. Mobile app - Stay on top of your hiring process with the BreezyHR mobile app, available for both iOS and Android devices.
What's not so good:
Limited AI capabilities - Compared to some competitors, BreezyHR has limited AI-driven features for candidate matching and profile enrichment.
Pricing:
💰 BreezyHR Pricing Summary:
Bootstrap : FREE! - All the basics for one position or pool
: FREE! - All the basics for one position or pool Startup : $157/mo - Enhanced hiring tools to get off the ground
: $157/mo - Enhanced hiring tools to get off the ground Growth (Most Popular 🏆): $273/mo - Hire better together with a growing team
(Most Popular 🏆): $273/mo - Hire better together with a growing team Business: $439/mo - Ultimate hiring control & flexibility
All paid plans include unlimited users, candidates, and customer support. Annual pricing offers 2 months free! Ideal for companies from 10 to 10,000.
JobAdder is a powerful and efficient AI-driven recruiting software that streamlines the hiring process for recruiters, HR teams, and agencies. Its AI and skill matching features enable users to source top talent faster and more accurately. With a user-friendly interface and an emphasis on automation, JobAdder ensures you can focus on meaningful tasks, leaving the repetitive work behind.
JobAdder Candidate Relationship Management
What sets JobAdder apart is its intelligent skill matching algorithm and AI technology, leading you to the best candidates in your database quickly. Its flexible pricing and no lock-in contracts make it a popular choice for businesses looking to optimize their talent acquisition process.
JobAdder Job Applicants Pipeline
Top 3 features and benefits:
AI and skill matching - Quickly discover candidates that match your open roles with JobAdder's AI recruiting tools.
- Quickly discover candidates that match your open roles with JobAdder's AI recruiting tools. Automated workflows - Save time by automating repetitive tasks, allowing you to focus on high-value activities.
- Save time by automating repetitive tasks, allowing you to focus on high-value activities. Extensive job board integration - Post jobs on 200+ job boards natively, reaching qualified candidates across multiple platforms.
What's good:
No lock-in contracts - Flexible terms without annual contracts, giving customers the freedom to choose.
Award-winning local support - Exceptional customer service to assist you with any inquiries or issues.
Real-time metrics and insights - Customize data sets and KPIs to gain valuable insights into your hiring process and adapt your strategy accordingly.
What's not so good:
Limited information on security standards - No specific details provided regarding security compliance and data protection measures.
JobAdder Pricing
Pricing:
JobAdder offers flexible pricing options to suit different business needs. To receive a tailored proposal, you can request pricing through their website. This process includes a 30-minute discovery call, a follow-up demo focused on your business needs, and a customized proposal based on your specific requirements.
An AI-powered appointment facilitator that supports recruiters in organizing interviews with potential job candidates.
Clara
Enables employers to quickly gather and consider the opinions of the hiring team with respect to interviews and speed up the process of recruitment. By incorporating AI recruiting techniques to screen resumes and perform searches based on keywords, recruiters can rapidly reduce the list of applicants to the most suitable applicants.
Clovers.ai
HireVue's AI-driven recruitment platform utilizes text-based conversations and O*NET job matching technology to enable hiring personnel to quickly identify and connect with prospective employees, thereby shortening the recruitment process by 4 times. Furthermore, the software automates changes to potential candidate ATS statuses and transmits automated SMS or WhatsApp invites, reminders, and notifications to minimize ghosting and optimize conversion rates.
HireVue AI Chatbot
A platform that uses AI to match candidates with job opportunities, automate resume screening, and improve the overall recruitment process.
SmartRecruiters recruiting platform
An AI-powered recruiting platform that uses machine learning to help recruiters find and engage with the best candidates, it helps with sourcing, resume screening, and candidate tracking.
Hireez AI recruiting tools
A platform that uses AI to provide personalized communication with job candidates and a chatbot to answer candidates' questions.
Phenom People
An AI-powered recruiting platform that helps recruiters identify, engage and track the best talent, using machine learning to identify the best candidates and predict which of them are likely to be interested in a specific job.
Entelo recruiting platform
IBM's recruiting solution that uses AI to help companies identify the best candidates, and improve the overall recruiting process.
IBM Watson Talent
An AI-powered writing tool that helps recruiters write effective job descriptions and optimize them for diversity and inclusion
Textio
A recruiting software that uses AI to help companies find candidates, and track the hiring processes with support for resume screening, interview scheduling, and candidate communication.
Workable recruitment software
YouTeam is undoubtedly a leader in the field of connecting top development talent with businesses across the globe. With its unique focus on small- and medium-sized development agencies in Latin America and Europe, it's revolutionized the way tech leaders find contract engineering talent. The platform's multi-step vetting process ensures that only the best are part of the network, making it a go-to choice for companies seeking quality and reliability.
Youteam AI Homepage
YouTeam Vetting Process
What sets YouTeam apart is its meticulous vetting process and the use of AI in the Matching Process, ensuring that the right candidates are paired with the right roles. It's a must-have platform for anyone looking to hire top-notch engineers and developers. With its transparent process, extensive network, and commitment to quality, YouTeam stands out as a premier platform in the tech talent acquisition field.
Youteams Vetting Process
Top 3 features and benefits:
AI-Driven Matching Process - Utilizes AI to review hundreds of potentially suitable candidates, ensuring the best matches for each open position.
- Utilizes AI to review hundreds of potentially suitable candidates, ensuring the best matches for each open position. Multi-Stage Vetting - A rigorous vetting process that includes agency due diligence and continuous re-vetting, guaranteeing quality talent.
- A rigorous vetting process that includes agency due diligence and continuous re-vetting, guaranteeing quality talent. Global Network - Access to 50,000+ pre-vetted engineers employed at hundreds of development agencies across Europe and Latin America.
Youteams AI Assistant Chat
What's good:
Quality Control - Every developer is vetted at least twice, ensuring quality and reliability.
- Every developer is vetted at least twice, ensuring quality and reliability. Professional Agency Support - Enjoy the benefits of a B2B relationship with strong local employers.
- Enjoy the benefits of a B2B relationship with strong local employers. Fast and Efficient - Get your perfect candidates in 48 hours, with an average of 1.75 interviews to close a role.
What's not so good:
Limited to Tech related roles - The platform is specialized in tech roles, which may not cater to all business needs.
Pricing:
YouTeam operates on a transparent pricing model, with clear hourly and monthly rates for various roles, experience levels, and technologies. The platform also offers examples of candidate profiles along with their rates tailored to your exact business needs.
YouTeam's unique role in using AI for hiring top talent, combined with its extensive vetting process, positions it as a standout platform in the tech recruitment landscape. Whether you're a startup or an established business, YouTeam offers a streamlined and trustworthy path to finding the right engineering talent for your projects.
Relevance of AI recruiting software in today's job market
The job market is very competitive in the present day and businesses are having difficulty in finding qualified candidates for the job.
AI recruitment software can assist hiring teams and companies in identifying relevant candidates from a huge pool of applicants in the , allowing them to fill empty positions quickly.
Moreover, these tools can also diminish bias in the recruitment procedure, providing companies with a more diverse and comprehensive workforce.
Types of AI Recruiting Tools
Resume Screening Tools
How they work
Resume screening tools utilize natural language processing (NLP) and machine learning (ML) algorithms to review and analyze resumes and cover letters.
They can extract significant information, such as job titles, skills, and years of experience, and compare them to a job posting's requirements.
This assists recruiters in quickly finding the most qualified contenders from a large pool of applicants.
Examples
Some of the more famous resume screening tools are JobAdder, and SmartRecruiters. These tools offer features like keyword search, resume parsing, and candidate matching.
JobAdder integrates with well-known applicant tracking systems (ATS) to facilitate the recruitment process.
Pros and cons
One of the benefits of using resume screening tools is that it can save time and energy for the first round of screening.
Additionally, it allows for a higher volume of resumes to be reviewed and flags resume that meet certain requirements, making the process more efficient.
However, there is a potential lack of human interaction in the screening process, and if the tools are not configured or trained correctly, they might overlook qualified candidates.
Interview scheduling tools
How they work
Interview scheduling apps leverage AI and automation to assist with setting up interviews between job seekers and recruiters or hiring managers.
Generally, these solutions sync with calendars and emails to pinpoint the most suitable times for all parties.
Additionally, automated notifications and confirmations are often part of the package, ensuring everyone has the same understanding.
Examples
Clara is a digital scheduling assistant that utilizes natural language processing (NLP) to apprehend requests and schedule interviews.
Pros and cons
The advantages of interview scheduling tools are clear: they save time and energy, and cut down on the number of emails needed to arrange a meeting.
What's more, they make sure everyone has their availability lined up, avoiding any kind of misunderstanding or hold-ups.
The downsides, however, include a lack of versatility and the risk of overlooking prospective employees if the scheduling isn't done in a timely fashion.
Chatbots
How they work
Chatbots are AI-powered virtual sidekicks that use natural language processing (NLP) and machine learning (ML) to interact with job seekers and furnish them with information or help.
They can be integrated with a company's website or social media channels and can offer round-the-clock support to applicants.
Additionally, they can be employed to filter and qualify prospects, dispense knowledge concerning the company and the job vacancy, and even arrange interviews.
Examples
Recruiting has become much easier with the assistance of chatbots like Phenom People, and HireVue.
Phenom People is a system that utilizes Artificial Intelligence to provide individualized communication with potential employees and an automated chatbot to respond to the queries of applicants.
HireVue is an AI-driven digital interviewing system that uses a chatbot to provide a conversational interview experience for prospects.
Pros and cons
There are several advantages to employing chatbots in the hiring process, such as providing around-the-clock assistance to applicants, automating mundane duties like arranging interviews and supplying company info, and aiding in the screening and qualification of hopefuls.
Nevertheless, there are some drawbacks, such as the bot not always understanding what the candidate is asking or being unable to answer intricate or delicate queries. Also, there is a chance that the recruitment task could lack a human touch.
Key features of AI recruiting tools
Natural Language Processing (NLP)
Natural Language Processing (NLP) is a subset of Artificial Intelligence (AI) that centers around the interplay between computers and human language.
NLP helps machines interpret and generate human language, which is an essential aspect of many AI recruiting platforms. NLP-powered features in AI recruiting software tools consist of sentiment analysis, language understanding, and text classification.
Sentiment analysis is a feature that utilizes NLP to analyze the shade and atmosphere of written language, such as candidate resumes and interview feedback.
This assists recruiters in quickly evaluating a candidate's qualifications and suitability for the role, by recognizing positive or negative emotions.
Another example is language understanding, that feature enables the tool to comprehend the aim of a user or a candidate, recognizing the context and the message of the text and providing pertinent information.
Machine Learning (ML)
Machine Learning (ML) is a type of Artificial Intelligence (AI) technology that allows computers to learn from data without explicit programming.
In the recruiting process, this can be used to automate such jobs as screening resumes, matching potential candidates, and preparing interview times, ultimately improving the whole recruitment experience.
Talking about ML-based features in AI recruitment tools, some examples would be resume matching, which uses algorithms to compare resumes to job requirements, and candidate ranking, which uses ML to rate prospects depending on their qualifications and fit for the job.
Integration with other systems
AI recruitment tools can also be integrated with other systems such as Applicant Tracking Systems (ATS) and calendar systems to make the hiring process smoother.
This includes syncing candidate data, scheduling interviews automatically, and keeping track of candidates' progression through the recruitment sequence.
Benefits of using AI recruiting tools
Increased efficiency and speed in the recruiting process
AI recruiting tools offer increased speed and efficiency in the hiring process.
These tools can take care of mundane and time-consuming tasks such as screening applications, matching profiles to the job requirements, and arranging interviews.
This leaves recruiters with more time to develop relationships with potential candidates and hiring managers.
AI can also help speed up the recruiting process by quickly analyzing resumes and pinpointing the most suitable applicants, as well as scheduling interviews.
Improved candidate experience
AI recruiting tools offer increased speed and efficiency in the hiring process.
These tools can take care of mundane and time-consuming tasks such as screening applications, matching profiles to the job requirements, and arranging interviews.
Recruiters can save time through this and invest more energy into developing relationships with potential candidates and hiring managers.
AI can also help speed up the recruiting process by quickly analyzing resumes and pinpointing the most suitable applicants, as well as scheduling interviews.
Enhanced data insights and analytics
An AI recruiting platform can provide recruiters with valuable data analysis and insights. For instance, with the help of natural language processing and machine learning, the tools can automatically examine resumes and interview responses to detect patterns and tendencies that can shape the hiring process.
This information can be leveraged to monitor the advancement of candidates, recognize the most effective recruiting channels, and assess the proficiency of recruiters.
Reduced bias in the recruiting process
AI software tools provide a great advantage to the recruiting process when filling job opening with top tech talent, as they are able to reduce any hiring bias that may have been present.
By automating resume screening, AI tools eliminate the subjective opinion of recruiters, which can often be affected by identity characteristics such as race, gender, and age.
Furthermore, NLP and ML algorithms can be trained to recognize patterns in resumes and interview feedback, which can help to remove any bias from the recruitment process and expand the variety of candidates.
It is important to be mindful that AI tools are just tools, and have the potential to bring forth any bias from the data it was trained on. Thus, it is essential to assess the data used to train the model, and regularly verify the bias in the model's resul
Cost
Implementing and maintaining AI recruiting software can be a difficult hurdle to overcome due to the associated costs. Not only are these tools pricey to buy, but they require a certain level of knowledge to operate and keep up.
Also, many AI recruiting tools are subscription-based, which can really drive up the cost of ownership.
Data privacy and security
Utilizing AI recruiting programs presents another problem - the need to preserve candidate data, which could include confidential information like resumes and individual contact details.
Breaches of security can be detrimental to the company's standing, so it's essential to execute strong data safety policies, like encryption and access restrictions, to protect the data of potential hires.
Ensuring compliance with laws and regulations
Companies using AI recruiting tools should be aware that they may be subject to a range of legal requirements, including data security and anti-discrimination laws, which differ from place to place.
Failing to adhere to these regulations can lead to hefty fines and other punishments, so it's essential to make sure you're compliant.
Potential for job displacement
The implementation of AI-driven recruitment solutions may lead to certain occupations, like resume evaluation and appointment booking, being made redundant.
This could result in personnel modifications within the recruitment team and may have an impact on the feelings of employees.
Addressing ethical concerns
Utilizing AI recruiting tools comes with some ethical issues, such as the possibility of hidden prejudices in the data used to educate the models, the obscurity in AI decision-making, and the effect of AI-controlled automation on occupation and the labor force.
It is essential for organizations to be cognizant of these ethical issues and take action to deal with them, for instance, by introducing transparency and bias-adjustment systems and creating plans to re-train displaced workers.
All in all, although there are several advantages to using AI recruiting tools, businesses must be conscious of the potential difficulties and take steps to reduce them.
This can involve examining the cost, data privacy, and compliance risks connected with AI recruiting tools, in addition to assessing the possible effect of AI-controlled automation on occupations and the workforce.
Key learnings
In this article, we've looked at the different types of AI-driven recruitment tools, from resume screening to interview scheduling and chatbots.
We've also gone over the crucial aspects of these tools, such as Natural Language Processing (NLP), Machine Learning (ML), and integration with other systems.
On top of that, the benefits of using AI recruiting tools have been highlighted, including more efficiency and speed during the recruitment process, improved candidate experience, deeper data insights and analytics, and decreased bias.
Despite these advantages, there are still some potential problems associated with AI recruiting tools, like cost, data privacy and security, adherence to laws and regulations, the possibility of job displacement, and ethical concerns.
The future outlook for AI recruiting tools
AI recruiting technology is seeing an exponential rise in usage and is forecasted to keep growing in the near future.
These tools are becoming more advanced, offering beneficial analysis and carrying out tasks autonomously, thus assisting companies to make more informed hiring choices and refining the recruitment approach.
Final recommendations for companies considering implementing AI recruiting tools
Companies considering the use of AI recruiting tools should take into account the cost, data privacy & security, compliance with laws and regulations, job displacement possibilities, and ethical considerations.
It is essential for them to assess the requirements of their recruitment process and select the AI recruiting tool that best meets these needs.
Companies should also weigh the potential effects of AI-driven automation on professions and the labor force, and devise plans to retrain employees who might be affected.
Before making any decision, it is important to conduct an exhaustive cost-benefit analysis and to test the tool with a few employees to assess its performance.
Wrapping up
In this article, we will had an extensive analysis of:
the kinds of AI-driven recruiting software tools that are available to boost your talent pipeline
their most outstanding characteristics and advantages
how they are utilized in the recruitment process and in the talent acquisition process.
We also talked about the ethical worries concerning the application of AI in recruitment and the measures that organizations can take to make sure that their utilization of these tools is just and impartial.
| 2023-02-05T00:00:00 |
https://superfounder.io/guide/ai-recruiting-tools
|
[
{
"date": "2023/02/05",
"position": 32,
"query": "artificial intelligence hiring"
}
] |
|
AI Based Recruitment Software - AI Recruitment Company
|
AI Based Recruitment Software - AI Recruitment Company
|
https://webpipl.com
|
[] |
Our AI-powered community hiring marketplace provides a set of world-class recruitment solutions that make us the obvious choice for recruiters.
|
Looking for a Hiring Service? Look no further than WebPipl
If you are seriously looking for the right candidates for your open positions look no further than WebPipl. We offer the best hiring service in the industry, period.
The effectiveness of our service can be witnessed by the humongous success stories that we have created. The case studies we have proves beyond doubt that the business of our clients had a positive impact using our hiring services.
Do you know what makes our hiring service stand out from the competition? We make sure to clearly communicate our unique value proposition to potential clients. Also, we offer a satisfaction guarantee. If one is confident about the quality of service they offer they will not have any reservations offering a guarantee.
More ...
| 2023-01-16T00:00:00 |
2023/01/16
|
https://webpipl.com/ai-based-recruiting
|
[
{
"date": "2023/02/05",
"position": 57,
"query": "artificial intelligence hiring"
}
] |
43% of Millennials Are Worried They'll Lose Their Job to ...
|
43% of Millennials Are Worried They’ll Lose Their Job to Chat GPT
|
https://www.digitalinformationworld.com
|
[
"Zia Muhammad"
] |
We might start to see widespread layoffs in the tech sector which will be spurred by how easy Chat GPT tends to make things. Employers are only going to think ...
|
The arrival of Chat GPT in the market revealed that the AI revolution was now fully underway, but in spite of the fact that this is the case many are worried about how this AI chatbot could impact their job prospects. Chat GPT can serve as an adequate replacement for a number of jobs, and a study from Sortlist Data Hub revealed that 43% of Millennials are worried it could take their own job.Their concerns might actually have some weight to them, since a number of employers have definitely been considering using Chat GPT and similar forms of generative AI for basic tasks. Buzzfeed has already announced that it will be generating at least some content from Chat GPT, and that might make certain creative jobs less essential than might have been the case otherwise.With all of that having been said and now out of the way, it is important to note that the field of marketing is going to be especially badly hit by the rise of Chat GPT. 51% of employers have stated that if they do end up using Chat GPT, they will mostly be using it for various forms of marketing campaigns.PR is yet another department that could see human workers getting replaced by Chat GPT, and what makes matters worse is that the people working in those departments aren’t even seeing this coming. Only about 16% of marketing professionals think that their jobs can be replaced by Chat GPT, which suggests that a majority of them might not be prepared for what is about to occur.We might start to see widespread layoffs in the tech sector which will be spurred by how easy Chat GPT tends to make things. Employers are only going to think of the bottom line, and if using Chat GPT gets them comparable work for a much lower cost, they will inevitably end up going down that route.One field that is currently more or less safe from Chat GPT is that of IT. Design, finance and legal departments are very likely going to be safe for the short term too.Take a look at below graphics for more insights:Read next: Bill Gates Shared His Thoughts About ChatGPT And Said It’s Going To Be As Important As PCs Emergence
| 2023-02-04T00:00:00 |
2023/02/04
|
https://www.digitalinformationworld.com/2023/02/43-of-millennials-are-worried-theyll.html
|
[
{
"date": "2023/02/06",
"position": 40,
"query": "AI job losses"
}
] |
AI over everything
|
AI over everything
|
https://www.emergingtechbrew.com
|
[] |
So far this year, 270+ tech companies have reportedly laid off more than 86,000 workers, which includes headcount reductions of about 12,000 at Alphabet, 10,000 ...
|
Coworking is a weekly segment where we spotlight Emerging Tech Brew readers who work with emerging technologies. Click here if you’d like a chance to be featured.
How would you describe your job to someone who doesn’t work in tech?
The intersection of engineering, finance, and manufacturing. At this stage of the tech and product development, the amount of value engineering and design for manufacturability is highly correlated to the long-term design language of the product and thus the cost. If we can integrate the supply base early and often—from machine shops to electronic manufacturers, from specialty coaters to tube benders—we can get feedback at the right time so our design engineers can pick which industrial processes to use and which to develop specially for our application.
What’s your favorite emerging tech project you’ve worked on?
Even though I have worked in very cool tech projects most of my career, including rockets and sustainable aviation, nothing has come close to how I feel about fusion energy…Fusion so far has been experimental in nature—this means that there is no supply base developed that can produce more than a couple of pieces of hardware a year. If they can produce them in the first place.
It is not uncommon for companies to want to be part of the supply chain just because the hardware is so different from what is in their shop now; statements like “making parts like this is why I got into this business” make a manufacturing nerd like me very happy.
One thing we can’t guess from your LinkedIn profile?
I co-owned a small pizza shop with my now-wife—girlfriend back then—for a while. We both had full-time jobs in which we worked during the day and then took over from the day manager after 6pm every weekday. Then 12pm-12am on Saturdays and Sundays.
| 2023-02-06T00:00:00 |
https://www.emergingtechbrew.com/issues/ai-over-everything
|
[
{
"date": "2023/02/06",
"position": 68,
"query": "AI job losses"
}
] |
|
Chart: Which Sectors Are Working With OpenAI?
|
Chart: Which Sectors Are Working With OpenAI?
|
https://www.statista.com
|
[
"Felix Richter"
] |
OpenAI. by. Felix Richter,. Feb 6, 2023. Artificial intelligence (AI) worldwide ... AI Experts Share Worry About Misinformation, Not Job Losses. Apr 24, 2025. AI ...
|
HTML code to embed chart
Can I integrate infographics into my blog or website?
Yes, Statista allows the easy integration of many infographics on other websites. Simply copy the HTML code that is shown for the relevant statistic in order to integrate it. Our standard is 660 pixels, but you can customize how the statistic is displayed to suit your site by setting the width and the display size. Please note that the code must be integrated into the HTML code (not only the text) for WordPress pages and other CMS sites.
| 2023-02-06T00:00:00 |
https://www.statista.com/chart/29244/number-of-companies-using-open-ai-in-their-business-processes-worldwide/
|
[
{
"date": "2023/02/06",
"position": 73,
"query": "AI job losses"
}
] |
|
Machine learning job market: a closer look to land the hottest ...
|
Machine learning job market: a closer look to land the hottest roles
|
https://www.airswift.com
|
[
"Raphael Santos"
] |
This article will provide a detailed overview of some of the most in-demand machine learning roles by the market and share an understanding of how these jobs ...
|
Source: Frame Stock Footage/Shutterstock
Uncover the latest trends in machine learning roles to grow your data analytics initiatives.
Machine learning is one of the fastest-growing fields in every industry right now, not just tech, and is quickly becoming an essential part of many organisations' operations. There are dozens of roles that are in-demand but which ones should you focus on?
This article will provide a detailed overview of some of the most in-demand machine learning roles by the market and share an understanding of how these jobs fit in a high-performance machine learning team.
Creating a successful machine learning team requires thoughtful consideration when it comes to staffing and skill requirements. In this article, we’ll take an in-depth look at the different roles within an ML team, as well as provide advice on building a strong one.
1. What is the job of a machine learning specialist?
2. What is the ML role in AI?
3. Learn all about the most in-demand machine learning roles
3.1. Machine Learning Engineer
3.1.1. A ML Engineer speciality: data labeling
3.2 Data Scientist
3.3. Product Manager
3.4. Data Engineer
3.5. Machine Learning Researcher
3.6. DevOps Engineer
3.7. MLOps Engineer
4. How do these roles work together?
4.1. MLOps and DevOps engineers are a good match
5. The future for machine learning roles
5.1. Green transition and green talent
5.2. Scaling AI Projects: It's time for AI Architects
6. We got the right talent for the exact role you need
What does a machine learning specialist do?
A machine learning professional is responsible for designing, developing, and maintaining machine learning systems. This can include tasks such as feature engineering, model development, optimization, deployment and continuous monitoring of the models.
Source: Frame Stock Footage/Shutterstock
They are also expected to have an understanding of databases, software engineering principles and data visualisation tools. ML is a rapidly changing field with constantly improving techniques and algorithms that have the ability to mimic human intelligence in order to complete tasks and solve problems.
Machine learning roles are highly sought after because they are able to quickly identify patterns in large datasets and provide business insights or solutions in areas where traditional methods would be too time-consuming or costly. Companies from all industries recognise the value of machine learning for streamlining processes, automating tasks, increasing efficiency, improving customer service, and more.
What is the role of ML in AI?
Machine Learning is an integral part of modern artificial intelligence (AI). It is a branch of AI focused on the development of algorithms that can learn from data and make predictions about future events.
Machine learning algorithms vary in complexity but essentially, they are able to extract pattern and knowledge from data automatically, without relying on any human input.
In addition, machine learning can be used to address problems such as image recognition, natural language processing, forecasting and more. In order for artificial intelligence systems to be truly useful and reliable, they must integrate machine learning algorithms into their systems.
Learn all about the most in-demand machine learning roles
Machine Learning Engineer
A Machine Learning Engineer is a specialist in the field of machine learning who designs, develops, tests and deploys predictive models for business applications.
This professional needs to possess expertise in coding and statistical modelling techniques along with knowledge of appropriate software tools. Plus, a ML engineer typically has analytical skills to extract meaning from large amounts of data and design experiments to test hypotheses. Knowledge of how to use data visualisations such as Tableau or PowerBI is also helpful in this career path.
Good communication skills are important, as is clear problem solving ability when interacting with other stakeholders involved in the project.
A ML Engineer speciality: data labeling
Machine learning engineers who specialise as data labelers are responsible for labeling and organising data sets. They use algorithms to identify patterns in the data, and then apply labels to the data points. This helps machine learning models to more accurately interpret the dataset by assigning relevant categories to all the inputs and outputs.
Data labelers, also known as data annotators, must have detailed knowledge about the classification of each object within the given context to help train the model for more accurate predictions.
They usually use machine learning algorithms to tag objects in images and videos with labels, timestamps and other metadata. Once labeled, these images can be used by businesses or developers looking to create software related applications like AI-powered facial recognition systems or autonomous vehicle navigation systems.
By working together with data annotation teams, data engineers and scientists can create more efficient models and achieve better results from the use of large datasets.
Data Scientist
Data Scientists are professionals who are skilled in the analysis of data. They combine knowledge from multiple fields such as statistics, computer science and machine learning to solve real-world problems.
A Data Scientist must have strong programming skills, particularly in Python, JavaScript and SQL. Further, they need to be fluent in Statistical Analysis such as Regression Analysis, Classifier Evaluation and Model Training.
Additionally, a Data Scientist needs a good understanding of Big Data technologies such as Hadoop and Spark for data exploration tasks. Finally, the ability to communicate results clearly through graphical tools, like the ones already mentioned in other roles, Tableau or PowerBI, is essential for the success of a Data Scientist.
Product Manager
The Product Manager is responsible for leading the development and deployment of products powered by machine learning. They need to have experience in product design, deep knowledge of relevant technologies, in-depth problem-solving skills, and commercial acumen.
They also must understand customer needs and collaborate with data science teams to develop high-quality models. And they need excellent communication skills to bridge the gap between stakeholders from different fields such as engineering and marketing.
A Machine Learning Product Manager job thus requires balancing a number of priorities while offering innovative solutions backed by smart data use.
Data Engineer
Data engineers are responsible for building and maintaining systems that capture data from various sources, organize it effectively, and store it in databases and data lakes.
Data engineers must also be well-versed in software development tools such as Java, C#, Python and others, as well as understanding various database platforms like Oracle, MySQL or MongoDB. They must also have a thorough knowledge of security protocols which will help them safeguard collected data against unauthorized access or manipulation.
Machine Learning Researcher
A Machine Learning Researcher is a highly skilled worker who studies the field of artificial intelligence (AI) and the development of computer algorithms that are able to learn from themselves.
They must have a deep understanding of mathematics, be proficient in coding languages such as Python, Java, and C++, have exceptional communication skills, understand data analysis methods, and be comfortable working with complex problem-solving techniques.
Machine Learning Researchers must also remain up-to-date on the latest AI tools and technologies in order to stay ahead of the competition in their field.
DevOps Engineer
DevOps engineers are an essential part of any machine learning team as they are responsible for ensuring that the applications and systems used to deploy machine learning models are running smoothly. They must have a deep understanding of the underlying infrastructure, including cloud computing platforms such as AWS or Azure, and be able to configure and maintain them in order to ensure optimal performance.
DevOps engineers must also be well-versed in scripting languages such as Bash, Python or Ruby and be able to automate tasks related to the deployment of machine learning models. Additionally, they must have a good understanding of security protocols and be able to set up authentication systems that protect the data from unauthorized access.
Finally, DevOps engineers are also responsible for monitoring the performance of the applications and systems used for deploying machine learning models and ensuring that they are running optimally.
MLOps Engineer
A MLOps professional is a person responsible for maintaining and optimising the workflow of machine learning tasks in an organisation. They can handle tasks such as building and testing models, deploying new models to production, and automating model-management processes through CI/CD processes.
The skills that MLOps professionals need include:
Knowledge of machine learning frameworks, such as Tensorflow and PyTorch .
and . Familiarity with cloud computing services on platforms such as AWS or Azure .
or . Fluency with regular software engineering languages like Python , Java , and Ruby .
, , and . Experience developing and deploying ML models.
Competency in data engineering concepts like relational databases, ETL pipelines, batch processing, and streaming technologies.
A working understanding of algorithms and deep learning architectures.
How do these roles work together?
Those different machine learning roles contribute to the larger goal of creating effective predictive models and ML solutions. Let's take for instance a team with data engineers collecting unstructured data and cleaning it up data, then if you look at the other side of your team's desk, you'll see data scientists interpreting the results — using different algorithms to explore trends and build models.
Looking more closely at this teamwork, you'll be witnessing machine learning engineers creating production-ready software by deploying a trained model into a real-world environment.
The team members collaborate closely together as they rely on each other's skills and expertise to achieve their goals.
MLOps and DevOps engineers are a good match
An MLOps engineer and a DevOps engineer can fit well together in a machine learning team as they provide complementary skills. The MLOps engineer can focus on automating the machine learning process, while the DevOps engineer can help coordinate its implementation in production.
Furthermore, they can collaborate on tasks such as continuous integration/continuous delivery (CI/CD) pipelines, which are essential for successful machine learning applications.
Both engineers should strive to ensure the smooth deployment of high-quality models within the company's environment. So, together these roles form an agile team that can develop, deploy, monitor and refine algorithms quickly — further allowing for faster time-to-market of machine-learning initiatives.
The future for machine learning roles
The future job prospects for machine learning roles are incredibly promising. As automated systems become more and more complex, machine learning engineers will be in high demand. And this workforce will need to use their expertise to find solutions for new business realities.
Green transition and green talent
The world is undergoing a major shift towards green and sustainable growth as countries look to reduce their environmental impact. But this shift will not happen successfully, or quickly, without the help of technology – specifically machine learning.
As such, there is a growing demand for skilled professionals who understand both the fundamentals of machine learning technologies as well as their application within the context of green technologies. That's why we developed a whitepaper called "Green tech talent required to boost net zero", in which we analyse the profile of the new workforce for this new green global economy. Download it for free in our website.
Source: Frame Stock Footage/Shutterstock
Scaling AI Projects: It's time for AI Architects
As machine learning projects become more complex, organisations need qualified professionals to assist in the scaling of successful AI solutions.
AI Architects can create a strategic roadmap for AI initiatives, assess and implement the most appropriate technologies to help companies scale their AI initiatives.
AI architects serve as the mediators, strategists, and supervisors of an AI architecture. They can also develop systems to bridge the gap between data science/engineering expertise and automation applications, in order to oversee and amplify AI-powered projects.
Additionally, they may also suggest solutions to improve the overall quality of machine learning models through improved processes such as versioning control and performance metrics tracking.
And last but not least, AI Architects can offer guidance on ethical AI practices and collaborate with other teams on new projects to bring these technologies to various enterprise platforms.
We got the right talent for the exact role you need
Machine learning has potential applications in many different industries, including healthcare, finance, and marketing. We also see an increasing demand in fields such as autonomous vehicles and human augmentation.
Not to mention the rise in using machine learning for automated decision-making. So, the competition for high-skilled talent is becoming even more ferocious these days. That's why you need a better strategy to hire the best talent out there.
Airswift is here to help you with that. With more than 60 offices and over 9,000 contractors worldwide, we can provide the best workforce solution for your global business expansion, including screening and hiring top talent in the tech field.
We have a team of experienced recruiters who can help you find the perfect candidate for any role in the tech industry.
We also provide comprehensive training and onboarding services to ensure that your new hires are up to speed with the latest technologies and trends in their field. Partner with us for the best machine learning professionals!
| 2023-02-06T00:00:00 |
https://www.airswift.com/blog/machine-learning-roles
|
[
{
"date": "2023/02/06",
"position": 1,
"query": "machine learning job market"
},
{
"date": "2023/02/06",
"position": 32,
"query": "AI labor market trends"
},
{
"date": "2023/02/06",
"position": 68,
"query": "artificial intelligence hiring"
},
{
"date": "2023/02/06",
"position": 35,
"query": "machine learning job market"
},
{
"date": "2023/02/06",
"position": 37,
"query": "machine learning job market"
},
{
"date": "2023/02/06",
"position": 35,
"query": "machine learning job market"
},
{
"date": "2023/02/06",
"position": 34,
"query": "machine learning job market"
},
{
"date": "2023/02/06",
"position": 34,
"query": "machine learning job market"
},
{
"date": "2023/02/06",
"position": 35,
"query": "machine learning job market"
},
{
"date": "2023/02/06",
"position": 35,
"query": "machine learning job market"
},
{
"date": "2023/02/06",
"position": 34,
"query": "machine learning job market"
},
{
"date": "2023/02/06",
"position": 38,
"query": "machine learning job market"
},
{
"date": "2023/02/06",
"position": 32,
"query": "machine learning job market"
},
{
"date": "2023/02/06",
"position": 38,
"query": "machine learning job market"
},
{
"date": "2023/02/06",
"position": 37,
"query": "machine learning job market"
},
{
"date": "2023/02/06",
"position": 38,
"query": "machine learning job market"
}
] |
|
Building a Smarter Future with AI In Construction Industry
|
Building a Smarter Future with AI In Construction Industry
|
https://revolveai.com
|
[
"Noman Zafar"
] |
Through predictive analytics, AI algorithms analyze data from previous projects to predict the workforce required for future projects. It helps in better ...
|
Construction has been around us forever — but the construction industry has come a long way since the days of caves and huts. Now, they use all sorts of tech to make construction tasks easier and smooth while keeping people safe when working, and that’s pretty good. However, the adoption of AI in the construction industry has been on an upward trajectory in recent years. As of 2020, AI in the construction industry is valued at $466.9 million. And according to Market Research Future, the value of the market is expected to rise to $2512.8 million by 2030. Whether it’s optimizing work schedules, improving workplace safety, or monitoring construction facilities, AI in construction is already proving its value. Let’s look at how we can leverage Artificial intelligence to make construction more efficient. Constructing Smart With The Cutting-edge Artificial Intelligence Suppose a drone hovers over your construction site. After a few moments, your tablet beeps with a series of observations the drone has made. For instance, it tells a laborer in section A is not wearing his helmet. Four of your diggers aren’t working. In section D, a dark patch of the earth suggests waterlogging is taking place. Engineers and architects can then make more informed decisions and optimize the whole design process on behalf of these useful data insights. These insights are the promise of AI in construction and literally changing the whole game for the construction industry. From design to construction and even maintenance, AI streamlines every aspect of construction. It makes processes faster, more efficient, and cost-effective, helping construction professionals work smarter, not harder. If you’re in the construction game, it’s worth looking at the following examples of AI in construction and how it could help you achieve your construction goals.
Examples of AI in Construction That Are Revolutionizing the Industry’s Landscape Expanded Design Potential 3D modeling undoubtedly has disrupted the construction industry. Considering it as a revolution, it helped the industry move from painstaking pencil drawings to ‘walkable’ designs. It allowed engineers and architects to make more detailed designs, including all angles. Building information modeling, or BIM, is another way to help construction professionals better design, build, and repair. It speeds up the overall design process using machine learning. It conceptualizes design areas in 3D, including electrical, plumbing, architecture, and mechanical systems. With 3D models, you can get a sneak peek of what the finished building will look like and how it’ll function. It helps you make smart design choices that can save a ton of money and make maintenance a breeze for the building owners down the line. Providing Safer Construction Sites Construction sites can be super dangerous, with higher injury and death rates than other industries. Construction workers are killed five times more often than other laborers. Things like loud noises that lead to hearing loss, heights that increase the risk of falling, and exposure to harmful materials like dust make construction work risky. It can result in sky-high insurance premiums, lower productivity, legal trouble, and lots of employee complaints for employers. Various construction sites now use computer vision cameras to detect code violations like workers not wearing their required safety gear. However, Wearable sensors like Spot-r help detect the location of your workers and alert you timely if an employee slips or falls. That’s where AI in construction comes in handy — it predicts and prevents accidents and health hazards before they occur. Tackling the Labor Shortage Labor shortage happens more often in the construction industry. It could be due to various factors, for instance, an aging workforce, declining interest in the industry, or a growing economy leading to more job opportunities in other fields. But Artificial intelligence is helping address this challenge in many ways:
Through predictive analytics, AI algorithms analyze data from previous projects to predict the workforce required for future projects. It helps in better planning and allocation of resources.
AI-powered processes can automate repetitive tasks such as data entry, which frees workers to focus on more complex tasks.
AI can be used in virtual construction simulations. It allows engineers to test designs and identify potential problems before construction begins, reducing the need for rework and streamlining the building process.
More Productive Jobsites AI is definitely changing the game in construction management with the introduction of automated vehicles and tools. The construction process is now more efficient and accurate, saving time and preventing human error. AI-powered construction vehicles such as bulldozers, excavators, and dump trucks can work independently, freeing laborers to focus on other tasks. Furthermore, smart tools like drilling machines, cranes, and concrete mixers can be programmed to carry out specific tasks and even make decisions based on real-time data. Moreover, AI algorithms can analyze data from construction sites and optimize processes, reducing waste and increasing productivity. It can include tracking worker productivity, monitoring material usage, and analyzing site conditions to minimize downtime.
AI in Construction Management It’s super important to get a grip on all the data generated during the construction process — from drawing and modeling to building and maintenance. Unfortunately, many construction pros are missing out on the benefits of using all that information. Consequently, tons of valuable data go to waste when it could have been used to improve things. Besides transforming the design process with available data insights, you can innovate a whole new construction project. Also, AI allows us to take advantage of the most current data from earlier models and structures (buildings) that are already constructed. Prevent Overcosting International research firm IDC surveyed the challenges construction project owners and developers faced. The survey findings reveal that 77% of construction projects were delivered late, while 75% exceeded the estimated budgets. Despite employing the best finance team, most construction projects get over budget. However, in such situations, AI is your ultimate savior! AI can help prevent over-costing by providing accurate estimations and predictions using data analysis. It can help you avoid unexpected expenses and properly allocate the budget. But the real magic happens when AI is applied during the construction process. AI algorithms can monitor the project’s progress in real-time and compare it to the budget estimate. Suppose the actual expenses start to exceed the estimate. In that case, AI can quickly identify the root cause and suggest adjustments to avoid overspending. So, by utilizing AI, construction companies can make more informed decisions, stay within budget, and ultimately deliver projects on time and under budget. Robotics and AI In Construction Robotics in the construction sector is taking off — and it has the potential to take off to great heights. These robots are typically autonomous machines capable of automating tasks on construction sites. Now you can retrofit various heavy equipment machines with artificial intelligence to perform duties like a human worker. For example, you can retrofit machinery like bulldozers, compactors, and loaders to perform hauling, digging or bricklaying, etc. However, drones can do much more than just inspect your site; they can deliver real-time maps and information on what needs to be done. Also, you’ll find industrial robots in warehouses and construction sites where repetitive tasks are required.
| 2023-02-06T00:00:00 |
2023/02/06
|
https://revolveai.com/ai-in-construction/
|
[
{
"date": "2023/02/06",
"position": 72,
"query": "workplace AI adoption"
}
] |
New Report: 92% of Jobs Require Digital Skills, One-Third ...
|
New Report: 92% of Jobs Require Digital Skills, One-Third of Workers Have Low or No Digital Skills Due to Historic Underinvestment, Structural Inequities
|
https://nationalskillscoalition.org
|
[] |
The analysis finds that 92% of jobs analyzed require digital skills. Previous NSC research found one-third of workers don't have the foundational digital skills ...
|
Closing the digital skill divide would generate significant, measurable economic payoff for workers, businesses, and the broader economy.
WASHINGTON, DC – February 6, 2023 – Today, National Skills Coalition (NSC) in partnership with the Federal Reserve Bank of Atlanta released Closing the Digital Skill Divide, a real-time snapshot of demand for digital skills in the US labor market. The analysis finds that 92% of jobs analyzed require digital skills. Previous NSC research found one-third of workers don’t have the foundational digital skills necessary to enter and thrive in today’s jobs. Together, these findings point to a significant digital skill divide. The new report also found that public investments in closing this digital skill divide can generate measurable economic payoff for businesses, workers, and the broader economy.
The report finds strong demand for digital skills across every industry (dispelling misconceptions that demand exists primarily in the tech sector) and in almost every occupation, including entry-level and frontline positions. The report also finds that the digital skill divide disproportionately impacts workers of color, low-income individuals, and rural residents, due to historic underinvestment and structural inequities.
The findings come at a pivotal moment as states plan to implement the historic $2.75 billion Digital Equity Act, part of the bi-partisan infrastructure law. The program provides funding to advance digital equity among populations most impacted by the digital divide.
The findings suggest that states that target resources toward digital skill building could generate measurable monetary benefits:
Workers that qualify for jobs that require even one digital skill can earn an average of 23 percent more than in a job requiring no digital skills. Moving from a job requiring no digital skills to one requiring at least three can increase pay by an average of 45%.
For the economy as a whole, these increased earnings could generate more state and federal tax revenue. Depending on the household size and composition, this could range from $1,363 to $2,879 in additional tax revenue per household per year.
For businesses, turnover costs (estimated at $25,000 when a worker quits within the first year to over $78,000 after five years) can be averted or delayed by ensuring that workers have upskilling opportunities.
“State policymakers are asking a lot of questions about how to most effectively target new federal resources to close the digital divide. With this groundbreaking research, any question about whether digital skills are as important as broadband and devices has now been answered,” said Andy Van Kleunen, National Skills Coalition CEO. “This report drives home that access to digital skill building is essential to advancing equity, opportunity, and economic growth.”
“This research shows how fundamental and foundational digital skills have become in the labor market,” said Sarah Miller, Principal Advisor, Federal Reserve Bank of Atlanta. “These are critical skills the workforce needs to have now and into the future. Policymakers and program administrators should view digital skill development as baseline as digital access to ensure economic mobility for the communities and workers they are serving.”
Over the next year, National Skills Coalition will work with policymakers, its member state coalitions, and corporate partner Comcast NBCUniversal to ensure more local and national leaders are aware of and take advantage of public sector digital equity funds to invest in the skill development programs that are critical to closing the digital divide.
“We’re proud to partner with the National Skills Coalition and drive deeper awareness of the digital skills gap that we have long invested in helping to close,” said Broderick Johnson, Executive Vice President, Public Policy & Executive Vice President, Digital Equity for Comcast. “The data is clear. Both fundamental and industry-specific digital skills are vital to individual economic mobility as well as the continued competitiveness of our nation’s economy. To address this critical challenge, policymakers at every level must commit public funds to training the workforce of today and tomorrow in partnership with nonprofits and corporations alike.”
While the report focused on national data, it found that demand for digital skills is high in every state and analyzed extensive data for two states – North Carolina and Illinois – as examples.
“Ninety percent of jobs in Illinois require digital skills,” said Juan Salgado, Chancellor for City Colleges of Chicago. “Many of our students are able to balance work, parenting, and education because they are choosing online learning, which also requires a high level of digital literacy. This report unequivocally demonstrates that digital skill building has a direct economic impact on students, families, businesses, and the community as a whole.”
The data analysis for the report was carried out as a joint project between NSC and the Center for Workforce and Economic Opportunity at the Federal Reserve Bank of Atlanta. The research team analyzed 43 million online job postings published in 2021 collected by Lightcast (formerly known as Emsi/ Burning Glass Technologies).
###
About National Skills Coalition: National Skills Coalition fights for inclusive, high-quality skills training so that people have access to a better life, and local businesses see sustained growth. We engage in analysis and technical assistance, organizing, advocacy, and communications to improve state and federal skills policies.
About the Center for Workforce and Economic Opportunity at the Federal Reserve Bank of Atlanta: The Center for Workforce and Economic Opportunity focuses on employment policies and labor market issues that affect low- and moderate-income individuals. It acts as a bridge between research and practice, connecting researchers, businesses, and policymakers with innovative approaches to creating economic opportunity through education and employment. The center also contributes to economic research and monetary policy discussions by tracking labor market trends affecting low- and moderate-income workers.
| 2023-02-06T00:00:00 |
https://nationalskillscoalition.org/news/press-releases/new-report-92-of-jobs-require-digital-skills-one-third-of-workers-have-low-or-no-digital-skills-due-to-historic-underinvestment-structural-inequities/
|
[
{
"date": "2023/02/06",
"position": 22,
"query": "AI labor market trends"
}
] |
|
Actually, we should be worried about AI coming for our ...
|
Actually, we should be worried about AI coming for our UX jobs
|
https://uxdesign.cc
|
[
"Chris Liu"
] |
Thanks to AI, firms are not only changing the job requirements for their roles — they are also hiring less overall. We're finally seeing the effects on “skilled ...
|
Actually, we should be worried about AI coming for our UX jobs
Evidence from economics suggests prudence and caution, not blind optimism, is the appropriate reaction to AI Chris Liu 4 min read · Feb 6, 2023 -- 15 Listen Share
“Robot as a slightly sinister automated teller machine realistic” (Midjourney, variation by the author)
When automated teller machines (ATMs) first came onto the scene in the 1970s, there were roughly 300 000 bank tellers in the US. The most common types of transactions — withdrawal, deposit, checking a balance — could now be automated away. But bank tellers didn’t go extinct. By 2010, there were 400 000 ATMs in America, and in that same time frame, the number of American bank tellers doubled to 600 000.
The story of the bank teller is often held up in optimistic portrayals of AI and its effect on labour. Technology can complement labour rather than substituting or replacing it. ATMs raised demand for banking services by lowering cost and they allowed human tellers to focus on high-value and complex tasks to perform for customers.
You might not see it put in quite the same terms, but this optimistic view underlies the majority of what you encounter about AI right now. Just this morning, I read a CityLab piece about how architects are using Midjourney to push creative envelopes and imagine surreal designs. When I look at the articles under Medium’s “UX” topic, I see posts helping designers to “co-create” with AI, how designers can use a ChatGPT API to “speed up your daily UX tasks,” and one that’s a list of the seven best “AI writing tools for designers.” What all of these pieces have in common is the idea that artificial intelligence can enhance our creative jobs.
Evidence from economics leads to a more sobering view.
In the past decade, when looking at the level of individual companies, AI exposure has correlated with reduced hiring. Thanks to AI, firms are not only changing the job requirements for their roles — they are also hiring less overall. We’re finally seeing the effects on “skilled” labour that we’ve already seen for “routine” labour; no longer can we say that our creative roles are AI-proof. Empirical evidence is building for what economists have long-predicted.
To be clear, I am not saying your job is disappearing tomorrow. But in contrast to most people’s anxiety over automation, many of us working in tech seem very hopeful about shiny new stuff like AI. This comes with the territory — we wouldn’t be working on digital technologies if we didn’t think there was good to be had for the world.
But this tech-optimism is a collective blind spot.
Instead, we should be clear-eyed and sober about what AI could mean for us working in UX. The exact prediction is hard, but just assuming all implications are great for all of us is naïve. Sure, read the above content about how you can use AI to enhance your current tasks, but I suggest an additional strategy: Expect the tasks that we take on to change over time. I plan to focus on those hard-to-automate (for now) tasks and developing the accompanying skillsets. AI doesn’t seem quite ready yet to replace an effective and clear research shareout to the leadership team; or able to facilitate a brainstorming workshop; or communicate in a nuanced, empathetic manner during design critiques — those skills are the ones that, in my opinion, seem worth prioritizing.
At the end of the day, we belong to “labour,” not “capital,” and there’s no reason why we won’t be displaced by the latter if there are cost-savings or profit to be made.
All the news about the layoffs at major tech companies in recent months — including stories of people who learned the news not through a conversation, but by discovering that they were locked out of their computer — should have convinced you of that.
The sky is not falling, but we shouldn’t rush blindly into an uncertain future like lemmings to a cliff. What we do have control over are the skills we choose to focus on, develop, and demonstrate at work. Prudence and caution, not blind optimism, is the appropriate reaction to artificial intelligence.
Update Feb 9: My designer just shared this AI tool that promises to create “delightful, editable UI designs from a simple text description.” The future is now.
— — —
Academic references:
Acemoglu, Daron, David Autor, Jonathon Hazell, and Pascual Restrepo. 2022. “Artificial Intelligence and Jobs: Evidence from Online Vacancies.” Journal of Labor Economics 40 (S1): S293-S340.
Acemoglu, Daron and Pascual Restrepo. 2018. “The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment.” American Economic Review 108 (6): 1488–1542.
— — — . 2019. “Automation and New Tasks: How Technology Displaces and Reinstates Labor.” Journal of Economic Perspectives 33 (2): 3–30.
— — — . 2020. “Robots and Jobs: Evidence from US Labor Markets.” Journal of Political Economy 128 (6): 2188–244.
— — — . 2022. “Tasks, Automation, and the Rise in U.S. Wage Inequality.” Econometrica 90 (5): 1973–2016.
Autor, David. 2015. “Why Are There Still So Many Jobs? The History and Future of Workplace Automation.” Journal of Economic Perspectives 29 (3): 3–30.
Arntz, Melanie, Sebastian Blesse, and Philipp Doerrenberg. “The End of Work is Near, Isn’t It? Survey Evidence on Automation Angst.” ZEW — Centre for European Economic Research Discussion Paper №22–036.
Park, Geunyong. 2022. “Investment Stimulus, Automation, and Skill Demand.” Job market paper.
| 2023-02-09T00:00:00 |
2023/02/09
|
https://uxdesign.cc/actually-we-should-be-worried-about-ai-coming-for-our-ux-jobs-97cab3519c6d
|
[
{
"date": "2023/02/06",
"position": 77,
"query": "AI labor market trends"
},
{
"date": "2023/02/06",
"position": 59,
"query": "artificial intelligence layoffs"
}
] |
The Majority of Jobs Now Require Digital Skills, Study Finds
|
The Majority of Jobs Now Require Digital Skills, Study Finds
|
https://www.govtech.com
|
[
"Julia Edinger Is A Senior Staff Writer For"
] |
... labor market information agencies are analyzing about your workforce?'” The ... Do Not Sell My Personal Information | Privacy & AI · gov-footer-logo-2024 ...
|
Photo courtesy of National Skills Coalition.
Photo courtesy of National Skills Coalition.
A record 92 percent of jobs now require definitely digital or likely digital skills, according to a new report from the National Skills Coalition.While digital skills training programs are increasing nationwide , gaps remain that government agencies can and should address . Although progress has been made gaps still exist.The report, titled, was released in partnership with the Federal Reserve Bank of Atlanta. It was created using empirical data from 43 million online job postings listed in 2021 to assess the economic demand for digital skills across industries.Although the specific digital skills needed varied by industry, there were two main categories of the skills needed: foundational and industry-specific skills, Amanda Bergson-Shilcock, NSC senior fellow and an author of the report, explained.Foundational digital skills may range from typing, to using mobile applications, to using common software packages like Microsoft. Industry-specific skills include specific platforms or software packages common to an industry, which may be different for workers in the real estate industry and workers in the food service industry.Bergson-Shilcock underlined the importance of digital resilience, which she defines as the ability to continually learn different types of industry-specific skills.“This is about being nimble enough to respond as your job changes over time, and your career evolves over time, and as the kind of digital skills you need change over time,” she said, underlining that a lot of digital upskilling involves building bridges from the skills people have to the skills they need or will need in the future.From this perspective, she underlined that skill-building programs must be specific to the needs of those participating. She suggested that policymakers start by doubling down on investments in the systems and processes already being used to gather input from employers to obtain a clearer understanding of specific needs of the community being served. After all, it is not helpful for people to be trained for jobs that do not actually exist in their communities.Training programs also need to provide contextualized, integrated education so that people understand the real-world application of the digital skills they are learning, she added.In providing digital skills training, government agencies will also be investing in economic mobility. Bergson-Shilcock stated that the study shows definitively that there is a strong correlation between jobs that require digital skills and higher wages.The report’s findings reveal that jobs that require at least one digital skill pay 23 percent more than those that do not, which in turn leads to greater tax revenue.Bergson-Shilcock also noted that because of occupational segregation, workers of color are more likely to be in jobs that don’t pay as well, or jobs where employers may not invest in upskilling.“We cannot afford to not invest in anybody’s skills here, because there’s no job in our labor market that does not now — or soon will — require digital skills.”To provide inclusive access to training for all individuals, organizations also need to think about other barriers to participation such as child care and transportation.While some states previously targeted older adults for digital skills training programs, Bergson-Shilcock notes that training is also needed for younger adults. While younger generations are often considered to be digital natives, NSC’s research suggests they often have fragmented knowledge.As agencies look to upskill their workforces , the skills necessary to participate are changing — especially in the era of hybrid and remote workforces “When we think about what state policymakers can take from this report, I think the first thing is, ‘How does this information help illuminate the data you already have that your state labor market information agencies are analyzing about your workforce?’”The information in this report can be leveraged as states create their digital equity plans as required by the federal government. But in addition, agencies can use this in thinking about funding opportunities to invest in education and workforce development.
| 2023-02-06T00:00:00 |
2023/02/06
|
https://www.govtech.com/workforce/the-majority-of-jobs-now-require-digital-skills-study-finds
|
[
{
"date": "2023/02/06",
"position": 87,
"query": "AI labor market trends"
}
] |
What's Wrong with ChatGPT? by Daron Acemoglu & Simon ...
|
What’s Wrong with ChatGPT?
|
https://www.project-syndicate.org
|
[
"Daron Acemoglu",
"Simon Johnson",
"Mariana Mazzucato",
"Rainer",
"Laurence Tubiana",
"Maciej Kisilowski",
"Desmond Lachman",
"Nicu Popescu",
"Goran Buldioski",
"Laura Tyson"
] |
Fewer entry-level jobs will mean fewer opportunities to start a career – continuing a trend established by earlier digital technologies. Consumers, too, will ...
|
Artificial intelligence is being designed and deployed by corporate America in ways that will disempower and displace workers and degrade the consumer experience, ultimately disappointing most investors. Yet economic history shows that it does not have to be this way.
CAMBRIDGE – Microsoft is reportedly delighted with OpenAI’s ChatGPT, a natural-language artificial-intelligence program capable of generating text that reads as if a human wrote it. Taking advantage of easy access to finance over the past decade, companies and venture-capital funds invested billions in an AI arms race, resulting in a technology that can now be used to replace humans across a wider range of tasks. This could be a disaster not only for workers, but also for consumers and even investors.
The problem for workers is obvious: there will be fewer jobs requiring strong communication skills, and thus fewer positions that pay well. Cleaners, drivers, and some other manual workers will keep their jobs, but everyone else should be afraid. Consider customer service. Instead of hiring people to interact with customers, companies will increasingly rely on generative AIs like ChatGPT to placate angry callers with clever and soothing words. Fewer entry-level jobs will mean fewer opportunities to start a career – continuing a trend established by earlier digital technologies.
Consumers, too, will suffer. Chatbots may be fine for handling entirely routine questions, but it is not routine questions that generally lead people to call customer service. When there is a real issue – like an airline grinding to a halt or a pipe bursting in your basement – you want to talk to a well-qualified, empathetic professional with the ability to marshal resources and organize timely solutions. You do not want to be put on hold for eight hours, but nor do you want to speak immediately to an eloquent but ultimately useless chatbot.
Of course, in an ideal world, new companies offering better customer service would emerge and seize market share. But in the real world, many barriers to entry make it difficult for new firms to expand quickly. You may love your local bakery or a friendly airline representative or a particular doctor, but think of what it takes to create a new grocery store chain, a new airline, or a new hospital. Existing firms have big advantages, including important forms of market power that allow them to choose which available technologies to adopt and to use them however they want.
More fundamentally, new companies offering better products and services generally require new technologies, such as digital tools that can make workers more effective and help create better customized services for the company’s clientele. But, since AI investments are putting automation first, these kinds of tools are not even being created.
Investors in publicly traded companies will also lose out in the age of ChatGPT. These companies could be improving the services they offer to consumers by investing in new technologies to make their workforces more productive and capable of performing new tasks, and by providing plenty of training for upgrading employees’ skills. But they are not doing so. Many executives remain obsessed with a strategy that ultimately will come to be remembered as self-defeating: paring back employment and keeping wages as low as possible. Executives pursue these cuts because it is what the smart kids (analysts, consultants, finance professors, other executives) say they should do, and because Wall Street judges their performance relative to other companies that are also squeezing workers as hard as they can.
Secure your copy of PS Quarterly: Post Americana Secure your copy of PS Quarterly: Post Americana A new issue of our magazine, PS Quarterly: Post Americana, is here. Subscribe to PS Premium to read expert commentary on the collapse of US global leadership and its implications for trade, security, cooperation, and the future of power. Subscribe Now
AI is also poised to amplify the deleterious social effects of private equity. Already, vast fortunes can be made by buying up companies, loading them with debt while going private, and then hollowing out their workforces – all while paying high dividends to the new owners. Now, ChatGPT and other AI technologies will make it even easier to squeeze workers as much as possible through workplace surveillance, tougher working conditions, zero-hours contracts, and so forth.
These trends all have dire implications for Americans’ spending power – the engine of the US economy. But as we explain in our forthcoming book, Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity, a sputtering economic engine need not lie in our future. After all, the introduction of new machinery and technological breakthroughs has had very different consequences in the past.
Over a century ago, Henry Ford revolutionized car production by investing heavily in new electrical machinery and developing a more efficient assembly line. Yes, these new technologies brought some amount of automation, as centralized electricity sources enabled machines to perform more tasks more efficiently. But the reorganization of the factory that accompanied electrification also created new tasks for workers and thousands of new jobs with higher wages, bolstering shared prosperity. Ford led the way in demonstrating that creating human-complementary technology is good business.
Today, AI offers an opportunity to do likewise. AI-powered digital tools can be used to help nurses, teachers, and customer-service representatives understand what they are dealing with and what would help improve outcomes for patients, students, and consumers. The predictive power of algorithms could be harnessed to help people, rather than to replace them. If AIs are used to offer recommendations for human consideration, the ability to use such recommendations wisely will be recognized as a valuable human skill. Other AI applications can facilitate better allocation of workers to tasks, or even create completely new markets (think of Airbnb or rideshare apps).
Unfortunately, these opportunities are being neglected, because most US tech leaders continue to spend heavily to develop software that can do what humans already do just fine. They know that they can cash out easily by selling their products to corporations that have developed tunnel vision. Everyone is focused on leveraging AI to cut labor costs, with little concern not only for the immediate customer experience but also for the future of American spending power.
Ford understood that it made no sense to mass-produce cars if the masses couldn’t afford to buy them. Today’s corporate titans, by contrast, are using the new technologies in ways that will ruin our collective future.
| 2023-02-16T00:00:00 |
2023/02/16
|
https://www.project-syndicate.org/commentary/chatgpt-ai-big-tech-corporate-america-investing-in-eliminating-workers-by-daron-acemoglu-and-simon-johnson-2023-02
|
[
{
"date": "2023/02/06",
"position": 92,
"query": "AI labor market trends"
},
{
"date": "2023/02/06",
"position": 44,
"query": "ChatGPT employment impact"
},
{
"date": "2023/02/06",
"position": 59,
"query": "AI workers"
}
] |
ChatGPT Has Broken The Economy
|
ChatGPT Has Broken The Economy
|
https://andrewzuo.com
|
[
"Andrew Zuo"
] |
AI and automation are already affecting the economy and employment and it's important to start considering alternatives like Universal Basic Income. This is not ...
|
Photo by Stefano Bucciarelli on Unsplash
Member-only story ChatGPT Has Broken The Economy
It’s Time To Rethink Employment Andrew Zuo 6 min read · Feb 6, 2023 -- 2 Share
ChatGPT has exploded recently and it is now time to ask the big question: what will happen to our jobs?
I mean, not my job or your job. But jobs in general. It doesn’t take a genius to realize that ChatGPT will cause layoffs which make the current wave of tech layoffs look like child’s play.
Millions of writers, customer service representatives, data entry analysts, and low level programmers, gone just like
| 2023-02-06T00:00:00 |
2023/02/06
|
https://andrewzuo.com/chatgpt-has-broken-the-economy-fa83fde8e769
|
[
{
"date": "2023/02/06",
"position": 20,
"query": "universal basic income AI"
},
{
"date": "2023/02/06",
"position": 43,
"query": "ChatGPT employment impact"
}
] |
Learning + Society
|
LEARNING + SOCIETY
|
https://www.xprize.org
|
[] |
Universal internet access makes learning more virtual, immersive ... Founder & Executive Director, Denver Basic Income Project · Nooshin Esmaeili.
|
In 2045, we imagine a future where every person, regardless of income, race, age, or identity has access to learning experiences customized to their unique capabilities and aspirations. In this future, every child is radically empowered by education, and their course in life is no longer determined by the zip code or village they’re born in.
High-quality learning is demonetized, delocalized, and woven into the fabric of society. Structural barriers no longer impede the aspirations of learners and their communities. Universal internet access makes learning more virtual, immersive, gamified, and hands-on. Education is no longer something that happens in a building during prescribed hours but evolves into a series of immersive, seamless, organic experiences that support continuous personal and professional growth.
Learners, employers, and civic leaders drive equitable human progress by creating decentralized structures, and leveraging technology, innovation, curated data, and insights mediated by artificial intelligence. Citizens have the knowledge, skills, and tools to navigate the complexities of government and society.
XPRIZE believes that revolutions in learning are fundamental building blocks of an inclusive and sustainable society. By cultivating inventors, innovators, and entrepreneurs, we will reimagine and remake the way societies design, produce, and consume products and services, globally. Incentivized prizes will rapidly advance critical learning platforms and grow innovation ecosystems for technology entrepreneurs, ushering in a new era where quality, accessible, lifelong learning is available to all.
| 2023-02-06T00:00:00 |
https://www.xprize.org/domains/society
|
[
{
"date": "2023/02/06",
"position": 53,
"query": "universal basic income AI"
}
] |
|
How AI Chatbots Like ChatGPT Could Impact Jobs
|
How AI Chatbots Like ChatGPT Could Impact Jobs
|
https://www.dashlane.com
|
[] |
ChatGPT could make just about any job easier by doing things like summarizing information, translating content, and generating generic answers to often-asked ...
|
How AI Chatbots Like ChatGPT Could Impact Jobs February 6, 2023
For years, artificial intelligence has helped automate work previously performed by people. From simple tasks, like transcribing audio, to more complex tasks, like summarizing thousands of legal documents, AI is helping make many of our jobs less tedious and complicated. AI advances like DALL-E mini and ChatGPT—the free AI chatbot developed by OpenAI that’s gone viral in recent weeks—could speed up that automation.
As AI technology becomes better and more advanced, the question in many of our minds is whether “robots” could replace us at work. ChatGPT is no exception. Some people were so awestruck by its capabilities, they declared that jobs like customer support and programming could very well become obsolete in a few years. Even academics were impressed by the bot’s essay-writing skills.
Does that mean that some of us should worry and start thinking about new careers? Not just yet. The technology has its limitations and lacks many qualities required to produce meaningful results. But, while most jobs remain safe for now, watching the trends can help us prepare for a future where AI bots could change how we work.
What is an AI chatbot?
You may not realize it, but you’ve already interacted with various AI chatbots online. These bots can help you do anything from finding information on a company’s website and choosing a new pair of shoes to taking your pizza order.
An AI chatbot is an automated program that uses natural language processing or natural language understanding, along with machine learning (all branches of AI) to interact with humans via text, speech, or both. These conversational bots are designed to understand both the context and the intent of a question or statement and respond based on the data they have.
By automating various aspects, chatbots bring benefits such as:
Scalability: Unlike humans, chatbots are great at multitasking and can engage with many customers at the same time.
Unlike humans, chatbots are great at multitasking and can engage with many customers at the same time. 24/7 availability: They can work around the clock without needing to stop for rest or sleep.
They can work around the clock without needing to stop for rest or sleep. Huge processing power: They can process massive quantities of data faster than any human, solving problems and responding to customer inquiries within seconds.
Although AI chatbots are a great automation tool, they still rely on human programmers. That means they only know what they’re taught, and the resulting bias and lack of contextual awareness could lead to a negative customer experience.
How AI chatbots could impact jobs
While AI chatbots have been around for some time, ChatGPT grew wildly popular after OpenAI (the same company that developed the DALL-E) made the chat research tool available for free. One million users signed up to try it within the first five days. Even Microsoft invested $10 billion in OpenAI recently, prompting speculation that ChatGPT could help the tech giant increase market share for its search engine, Bing.
Some people who’ve tried the app described its capabilities as stunning and mind-blowing. Perhaps the most exciting part is that ChatGPT could make automating interactions and certain tasks easier, faster, and more accessible. But it’s not likely to replace jobs wholly—rather, it could make some parts of jobs easier for humans.
Here are some examples:
Marketing: ChatGPT is good at writing high-level content based on information harvested from the internet, and it can even refuse a query based on a false premise. But it can’t fact-check or understand nuances, empathize with the audience, and so on. So perhaps marketers could instead use the tool for generating ideas and writing entry-level content.
ChatGPT is good at writing high-level content based on information harvested from the internet, and it can even refuse a query based on a false premise. But it can’t fact-check or understand nuances, empathize with the audience, and so on. So perhaps marketers could instead use the tool for generating ideas and writing entry-level content. Programming: The app can fix broken code, which could eliminate this tedious task for programmers. However, it can’t replace programmers altogether because we still need humans to create, among other things, the very models used by AI. Also, ChatGPT requires many code examples to be trained, and some companies won’t be okay with having their codebase appear in a public database, even if it’s anonymous.
The app can fix broken code, which could eliminate this tedious task for programmers. However, it can’t replace programmers altogether because we still need humans to create, among other things, the very models used by AI. Also, ChatGPT requires many code examples to be trained, and some companies won’t be okay with having their codebase appear in a public database, even if it’s anonymous. Education: One area where the bot shines is in explaining complex concepts, which could make it ideal for teaching. But the job of college professor is safe—ChatGPT is often inaccurate and can’t separate fact from fiction. And, like other similar programs before it, sometimes the chatbot spews complete nonsense. Still, the app could be a great tool for automating some teaching tasks, such as writing a lesson on an entry-level concept, as long as the instructor checks the final work.
ChatGPT could make just about any job easier by doing things like summarizing information, translating content, and generating generic answers to often-asked questions. And, of course, we’ll see more advances, improving not only this chatbot but others, too—and creating new use cases.
ChatGPT may not replace jobs, but we do expect to see more jobs relying on AI chatbots like this one in the future. If this means humans no longer have to do monotonous or boring work, why not?
Want to learn what else AI bots can do? Read about the DALL-E and its ability to create realistic images from prompts.
| 2023-02-06T00:00:00 |
2023/02/06
|
https://www.dashlane.com/blog/ai-chatbots-jobs
|
[
{
"date": "2023/02/06",
"position": 12,
"query": "ChatGPT employment impact"
}
] |
The Game-Changing Implications of ChatGPT! - globalEDGE
|
The Game-Changing Implications of ChatGPT!
|
https://globaledge.msu.edu
|
[] |
However, it's important to note that language models like ChatGPT are not designed to replace human jobs, but rather to assist and augment them.” Many different ...
|
Published: 2/6/2023 10:13:06 AM
Since being introduced to the public on November 30th of 2022, ChatGPT has taken over the world by storm. It is an AI chatbot designed and created by OpenAI, an AI research and deployment company. ChatGPT is a natural language processing tool driven by AI technology that allows for users to have human-like conversations, conduct research, answer questions, and assist with tasks. But, the question being asked is what are the applications of the newfound AI technology?
While the hype for the new AI is currently peaking, a major concern is starting to circulate as it pertains to the job market and who will be affected by the new technology. Advertising is currently one of the main markets at risk with the emergence of ChatGPT. Ad revenue comes from owning content that receives enough attention for companies to purchase space on. ChatGPT may possibly take the “middle-man” out of the equation when it comes to searching for information. Because the information utilized by the AI is readily available, the need to search the web and reach different sites becomes eradicated.
Google is one of the main companies affected by the newfound technology. As stated in our prior blog on ChatGPT, Google has recently declared a “Code Red.” As of 2022, Google’s revenue totaled at $69.1 billion and $39.5 billion was from search ads. ChapGPT is becoming a direct competitor to Google because of its question-answering capabilities. The AI has the potential to be able to create more personalized and targeted advertisements for its user; ChatGPT must have access to real-time data for this to be possible. By 2024, ChatGPT’s owner OpenAI projects $1 billion dollars in ad revenue.
Many people around the globe are beginning to wonder what effects this new technology will have on the job market. This has been a topic in the air for some time now and has caused many to begin to prepare themselves for the possibility of job loss. Recently ChatGPT was asked about its potential to take away human jobs. The AI replied, “ChatGPT and other language models like it have the potential to automate…However, it’s important to note that language models like ChatGPT are not designed to replace human jobs, but rather to assist and augment them.” Many different countries are beginning to hop on the trend. Currently, China is developing its own AI chatbot service through its already existing AI service known as Baidu. This new service is supposed to mirror OpenAI’s own ChatGPT and if deadlines are met, is projected to release before Google launches its own AI. Another new technology that has been developed is DALL-E. DALL-E was released on January 5th, 2021, and is an AI system that can create realistic images and art from a description in natural language. ChatGPT is not allowed everywhere in the world. Countries with stricter privacy laws have banned AI. For example, some notable places that don’t allow ChatGPT are Russia, China, Egypt, Iran, and Ukraine.
ChatGPT is currently valued at $14 billion. This newfound source of value will certainly have effects on the digital world. Many companies such as Meta, Canva, and Shopify are all already starting to implement the technology into their businesses. As the technology continues to develop and gain more notoriety, it is to be expected that many more companies will elect to implement ChatGPT into their companies.
With the new generation of technology storming the markets, the potential for change is almost certain. ChatGPT is taking over the technology market by storm and is currently leading this revolution and allowing for the emergence of other similar AI technology. As these AI innovations continue to develop, the world of international business is in for a huge awakening.
| 2023-02-06T00:00:00 |
2023/02/06
|
https://globaledge.msu.edu/blog/post/57228/the-game-changing-implications-of-chatgp
|
[
{
"date": "2023/02/06",
"position": 25,
"query": "ChatGPT employment impact"
}
] |
The Future of Chat GPT
|
The Future of Chat GPT
|
https://sipodsoftware.com
|
[
"Jovana Nanaši Rudan"
] |
This could lead to a decrease in demand for certain jobs, as well as a shift in the skills and expertise required for others. However, it is important to note ...
|
Open AI’s public release of Chatbot GPT at the end of 2022 had far-reaching effects on nearly every industry, causing a stir in the world. This innovative technology has generated a buzz, leaving us wondering what the future holds for Chat GPT and similar language models.
Chat GPT is undoubtedly set to revolutionize the tech world. Are you concerned about AI taking over our jobs, or are you excited about the future? Continue reading our blog to learn more about what the future of Chat GPT might look like.
What is Chat GPT?
ChatGPT is a highly advanced AI system that can produce text responses resembling human language. It operates using the GPT (Generative Pre-trained Transformer) model and has been trained on a massive corpus of conversational text. This allows it to provide information and respond to inquiries almost indistinguishable from a human conversation. The most well-known version of Chat GPT is the GPT-3.5 series.
This chatbot system uses NLP (Natural Language Processing) and deep learning to understand and process language. This allows it to perform various tasks, including customer service, which is far more advanced than traditional chatbots. The GPT-3 series is an excellent tool for researchers and developers working on NLP projects, and it has various specific tasks, domains, and applications available for use.
OpenAI has already released several versions of GPT, each with increasing capabilities and performance, and will continue to develop and improve the technology behind Chat GPT. Currently, the Chat GPT AI system does not compare its results to real-world data, but we can expect real-world data integration in the near future.
The technology behind Chat GPT
Chat GPT-3, also known as Generative Pre-training Transformer 3, is a cutting-edge artificial intelligence technology. It allows chatbots to comprehend and generate human-like natural language with remarkable accuracy and fluency. It is the largest language model to date, consisting of 175 billion parameters and the capability to process billions of words in a matter of seconds.
OpenAI has pre-trained a deep neural network with a vast text dataset and fine-tuned it for specific tasks, such as answering questions or generating text, with improved performance. This is the technology that is behind Chat GPT-3. Multiple transformer blocks that process the input text and generate output predictions create the network. The network incorporates self-attention mechanisms, enabling it to weigh the relevance of different words and phrases in the context of the conversation. Additionally, transformers allow Chat GPT-3 to generate coherent text even with limited input.
Chat GPT-3 is a significant advancement in the field of NLP as it uses transformer-based architecture to process vast amounts of data in parallel, leading to a more human-like understanding and generation of text. This technology has numerous uses, such as chatbots, machine translation tools, text summarization software, and more. However, Chat GPT-3 lacks internet connectivity and can only operate using the data it has received during training, limiting its ability to access external information.
The history of Chat GPT
It’s crucial to examine ChatGPT’s history to understand its future prospects. The history of Chat GPT includes some of Silicon Valley’s most prominent names. Elon Musk, Peter Thiel, and other tech investors founded OpenAI, the company behind the creation of Chat GPT, in 2015 as a nonprofit organization. Its goal was to counteract the centralization of AI by making its patents and research available to the public. The company wanted to develop AI “in the way that is most likely to benefit humanity as a whole,” according to the information stated on OpenAI’s website on December 11, 2015.
In 2018, Elon Musk left the board due to a conflict of interest with Tesla AI. In 2019, OpenAI shifted from nonprofit to “capped-profit,” allowing potential profits of 100X for investors, with the remaining money going towards not-for-profit work. That same year, Microsoft invested $1 billion in OpenAI, and the two companies announced a partnership, with OpenAI licensing its technology exclusively to Microsoft. The collaboration enables Microsoft to compete with Google’s AI company, DeepMind.
Since the latest Chat GPT release, Sundar Pichai, the CEO of Google, has taken part in multiple meetings to address Google’s AI strategy in light of the threat posed by ChatGPT. The company also brought in Google cofounders Larry Page and Sergey Brin to address the issue. It was reported that Microsoft planned to use ChatGPT to power its search engine, Bing.
In January this year, Microsoft announced its intentions to invest $10 billion in OpenAI in the upcoming years, giving the tech giant a 75% share of OpenAI’s profits until it recoups the investment and then a 49% stake going forward.
The future of Chat GPT
In recent years, Chat GPT technology has been making waves in various industries. It has the potential to streamline roles and fundamentally change how people create value. At the same time, there are concerns about its impact on human employment. Let’s explore some of the use cases of Chat GPT, its future, and whether or not you should be worried.
Use cases of Chat GPT
Customer Support – AI-powered chatbots can offer round-the-clock customer support and promptly address customer inquiries. They can significantly improve customer support by providing quick and personalized responses to customer queries and needs.
Marketing and sales – Chatbots can assist in lead generation, prospect evaluation, and closing deals by guiding customers through the buying process. They can also gather valuable information about potential customers and provide data-driven insights to sales and marketing teams, enabling them to tailor their approach.
Education – Educators can utilize chatbots to educate and respond to students’ questions in an engaging and appealing way. One potential use of ChatGPT in education is the creation of exams or quizzes.
Healthcare – AI-powered chatbots can offer customized health recommendations and support in diagnosing medical conditions. Additionally, AI-driven chatbots can also play a role in streamlining administrative tasks, such as appointment scheduling and prescription refills, improving the overall healthcare experience for patients.
Recruitment – Recruiters can utilize chatbots to automate various aspects of the recruitment process, increasing efficiency and saving time and resources. Additionally, AI-driven chatbots can help to screen and pre-qualify candidates, streamlining the interview process for recruiters.
Travel – Chatbots can assist travelers in booking flights, hotels, and other travel arrangements quickly and easily. In the future, AI-driven chatbots could provide real-time updates on flight status, weather conditions, and local events, making it easier for travelers to plan their trips and stay informed.
Entertainment – AI-powered chatbots can offer personalized recommendations for movies, music, and other forms of entertainment. They can also generate complete scripts for movies or shows and write lyrics for songs.
Programming – ChatGPT can generate code snippets based on specific programming languages and paradigms, allowing developers to write code more quickly and efficiently. It can also help with debugging assistance and code review.
The Chat GPT’s impact on employment
I dared to ask Chat GPT what the worst possible outcome of Chat GPT implementation for human employment is. This is the answer I received: “The worst possible outcome of Chat GPT implementation for human employment is job loss due to automation and AI-powered systems becoming more capable of performing tasks previously done by humans. This could lead to a decrease in demand for certain jobs, as well as a shift in the skills and expertise required for others. However, it is important to note that AI can also create new job opportunities, and that its impact on employment will likely be complex and multifaceted. Additionally, proactive steps can be taken to mitigate any negative effects, such as providing education and training for workers to acquire new skills and adapt to changing job markets.”
Should you be worried about your job?
The rise of AI has sparked fears that technology like Chat GPT will replace many jobs, including programmers, journalists, and creative writers. While it’s true that ChatGPT can generate consistent and coherent responses, it’s still far from being a job killer. In fact, ChatGPT has its limitations. The current quality of output has a lot of misinformation it is less reliable in solving complex problems.
ChatGPT can still be an asset to us in various ways. For example, journalists and creative writers can use Chat GPT for generating headlines and finetuning ideas. It’s important to note that this technology cannot replace manual labor, soft skills, or relationship building and maintenance. We can use Chat GPT technology to augment tasks, not replace them.
If embraced and used correctly, it can free up more time for people to focus on higher-value tasks that require more creativity and problem-solving. The use of ChatGPT effectively is a skill in itself. It’s up to us to understand its full potential and educate ourselves rather than being afraid of its impact on our jobs.
Conclusion
With all this talk about the future of Chat GPT, you may be reaching for a copy of Aldus Huxley’s Brave New World or George Orwell’s 1984. Instead of fearing the future of Chat GPT and dwelling on a dystopian view that technology will replace all human jobs, it’s important to remember that technology can bring both opportunities and challenges. While it may displace certain jobs, it can also create new ones and open up exciting career paths. If you’ve enjoyed this article, you may also want to look through our blog on the future of NFT.
| 2023-02-06T00:00:00 |
2023/02/06
|
https://sipodsoftware.com/the-future-of-chat-gpt/
|
[
{
"date": "2023/02/06",
"position": 58,
"query": "ChatGPT employment impact"
}
] |
RadioLabour
|
RadioLabour
|
https://www.radiolabour.net
|
[] |
India's Self-Employed Women's Association is the world's largest independent women's labour union with 2.1 million members. ... Outsourcing worker intelligence ...
|
RadioLabour International was a global news service which operated from January 2010 to September 2024.Programmes from RadioLabour Canada are available here
Interviews and
featured programmes
China continues attack
on Hong Kong unionists
In 2020 Beijing forced Hong Kong’s government to adopt an anti-union National Security Law which has resulted in the arrest of 292 activists and the collapse of the legitimate labour federation in the territory, the Hong Confederation of Trade Unions. An interview with the Executive Director of the Hong Kong Labour Rights Monitor, Christopher Siu-tat Mung.Duration: 8'24"
Public banks that
are really pro-public
Public banks are banks owned by public institutions such as government agencies. But not all are pro-public banks that finance vital public services or entreprises. Thomas Marois, the Director of the Public Banking Project at McMaster University in Hamilton, Canada, explains why labour organizations should support and lobby for pro-public banks.Duration: 13'35"
Plastic, plastic, everywhere
The International Negotiating Committee on Plastic Pollution is creating a global treaty on plastics. Comments by Daria Cibrario, policy officer for Public Services International.Duration: 15'55"
Labour announces a global
campaign For Democracy
The International Trade Union Confederation has launched a world-wide 'For Democracy' campaign. ITUC General-Secretary Luc Triangle describes the campaign and why it is needed.Duration: 9'48"
2024: Year of the facist?
The rise of fascism in the United States and other countries needs to be confronted by unions and other progressive organizations. A special RadioLabour programme about the difference between authoritarianism and fascism.Duration: 15'00"
Labour at UN's COP28:
Fighting for a just transition
The United Nations climate change conference COP 28 is taking place in the United Arab Emirates from November 30 to December 12, 2023. An interview with Jeremy Anderson, Director of Just Transition and Sustainable Transport for the International Transport Workers’ Federation.Duration: 12'51"
ITUC General Secretary
Luc Triangle calls for
ceasefire in Gaza
The International Trade Union Confederation has called for a ceasefire in Gaza with a return of the hostages and a two-state solution. ITUC General-Secretary Luc Triangle re-emphasizes the ITUC's long-standing call for peace in the world.Duration: 9'13"
Artificial Intelligence
can cause fake Education
A new report by the global union Education International shows that AI can degrade the quality of education, worsen working conditions for teachers and provide inferior schooling for students.Duration: 10'07"
Ukrainian unions
support the war, but . . .
Unions in Ukraine wholeheartedly support the war against Russia. But the Ukranian government is trying to weaken labour legisation. An onsite report by the editor of LabourStart, Eric Lee.Duration: 6'18"
How the first Starbucks
was unionized in the US
Michelle Eisen was one of the workers who unionized the first Starbucks in the United States.Duration: 9'41"
Fighting for respect
for LGBTI workers
The IUF global union 2023 Congress heard a report from the LGBTI Workers and Allies Committee. Comments by committee Chair Michelle Kessler.Duration: 5'51"
Working for womens' rights
in the Asia Pacific region
An interview with Andi Cipta Asmawaty of the Asia Pacific Forum on Women, Law and Development.Duration: 5'00"
International labour
supports Ukrainian workers
An interview with Vasyl Andreyev, the chair of the Ukrainian construction union (Profbud) - an affiliate of the Building and Wood Workers International global union (BWI).Duration: 5'00"
Artificial intelligence:
How workers can share control
Developments in machine learning and computer algorithms may be about to radically change many workplaces. Governments and employers need to share control with workers. Comments by the Assistant General Secretary of Public Services International, Daniel Bertossa.Duration: 7'43"
Labour's Nobel prize awarded to International Domestic Workers' Federation
The 2023 Arthur Svensson International Prize for Trade Union Rights has been awarded to the International Domestic Workers' Federation and its General Secretary Elizabeth Tang. The prize is known as the Nobel prize of the international labour movement.Duration: 5'28"
Beijing's attack on
Hong Kong unions
In 2020 Beijing forced Hong Kong’s government to adopt an anti-union National Security Law which has resulted in the arrest of unionists and the collapse of the legitimate labour federation in the territory, the Hong Confederation of Trade Unions. An interview with the Executive Director of the Hong Kong Labour Rights Monitor, Christopher Siu-tat Mung.Duration: 7'42"
How labour can confront
automation in the workplace
A report by AlgorithmWatch, commissioned by the ITUC, provides practical advice for unionists dealing with automation. An interview with AlgorithmWatch's Senior Policy and Advocacy Manager, Anne Mollen.Duration: 12'38"
Educators and the
earthquake in Turkey
On February 6, 2023, an earthquake in Turkey killed 50,000 people and injured many more. Education International sent a delegation to the country to discover what it could do to help. The delegation included Johanna Jaara Åstrand, EI's Vice-president for Europe, Maike Finnern, the president of the German Education Union and the General Secretary of EI, David Edwards.Duration: 4'45"
American teachers
helping children in Ukraine
More than 400 children have been killed by the war in Ukraine, hundreds have been wounded and thousands traumatized. Members of the American Federation of Teachers are helping by purchasing generators for the schools and organizing mental health programmes for the children. An interview with the president of the Cleveland Teachers Union, Shari Obrenski.Duration: 8'59"
Should unions call for
a four-day work week?
The four-day work week is being promoted as a solution to over-work, unemployment and work-life balance. Is the four-day work week the answer? Comments by the General-Secretary of UNI Global Union, Christy Hoffman.Duration: 5'55"
Transport unions helping
families of seafarers in Ukraine
When Russia attacked Ukraine in February 2022 thousands of Ukrainian seafarers were on their vessels away from their families. The European Transport Workers Federation and the International Transport Workers Federation immediately organized assistance. The assistance continues. An interview with the ITF's Maritime Coordinator, Jacqueline Smith.Duration: 7'03"
Severe shortage of
educational workers
in the United States
The United States has a shortage not only of teachers but other educational staff as well. However there are solutions. An interview with the Director of Research for the National Education Association, Stacey PelikaDuration: 16'36"
International Accord
extended to protect
garment workers in Pakistan
The global unions UNI and IndustriALL created a successful project to protect garment workers in Bangladesh after the 2013 Rana Plaza disaster. The project, called the International Accord for Health and Safety in the Garment and Textile Industry, has now been extended to Pakistan. An interview with the Deputy General Secretary of UNI Global Union, Alke Boessiger.Duration: 5'51"
Investing in education is best option to ensure peace
The Ethiopian Teachers Association is helping educators who were caught in the war in the northern part of the country. A report by the president of the ETA, Yohannes Benti.Duration: 4'31"
Struggling for democracy
and union rights in Turkey
Turkey is continuing its repression of unions. Two labour activists were invited to the UK by Unison to describe what is happening to unionists and workers in the country.Duration: 8'54"
Make Amazon Pay!
A coalition of unions and NGOs called Make Amazon Pay organized a day of action to protest Amazon's treatment of its workers.Duration: 5'20"
Eliminating violence
against women
November 25 is the International Day to Eliminate Violence Against Women. An interview with Brenda Modise of South Africa's FEDUSA.Duration: 6'55"
Global Action on Care
Our care systems need to be revised away from just profit-making. And care workers need decent pay and working conditions. Comments by the Social Care Organizer of Public Services International Huma Haq.Duration: 5'09"
Private consultants
degrade public services
The use of private consultants by governments results in poorer public services, job losses and greater expense for taxpayers. The European Public Service Union commissioned a report to show the extent of the problem. The report was presented at a media conference in Brussels by EPSU General Secretary Jan Willem Goudriaan.Duration: 10'27"
Women Labour Rights
and Digitalization
The Asia-Pacific Forum on Women, Law and Development held a conference on the effects of digitalization on women in Asia. A participant was Kamz Deligente from the Center for Trade Union and Human Rights in the Philipines.Duration: 5'59"
Modern slavery rises to 50 million
Modern slavery, which includes forced labour and forced marriage, has increased in the past five years to 50 million world-wide. An interview with the former General Secretary of the ITUC, Sharan Burrow.Duration: 4'40"
The world needs
69 million more teachers
The world needs to hire 69 million teachers and provide then decent pay and working conditions. A presentation by the General Secretary of the South African Teachers Union, Mugwena Maluleke.Duration: 4'25"
African workers paid
slave level wages
Even many of those who have jobs in Africa are paid slave-level wages. But the African Regional Organization of the International Trade Union Confederation has solutions. A presentation by ITUC-Africa Deputy General Secretary Joel Akhato Odigie.Duration: 4'28"
How collective bargaining
is helping workers world-wide
A survey of 125 countries by the International Labour Organization shows how collective bargaining is being used successfully to address the pandemic and other issues such as the gender pay gap. An interview with ILO-ACTRAV Senior Specialist in Workers' Activities, Ariel Castro.Duration: 7'27"
Eliminating child labour
in Zimbabwe
The Zimbabwe Teachers' Association has a systematic long-term approach to eliminating child labour in the country. Comments by ZIMTA's Training and Development Officer, Angelina Lunga.Duration: 9'32"
How to help the world's
160 million child labourers
At the 5th Global Conference on the Elimination of Child Labour held May 15-20, 2022 in Durban South Africa the global union Education International presented a five-point plan to eliminate child labour. Comments by Dennis Sinyalo the Africa Regional Director of Education InternationalDuration: 5'34"
Labour and the war in Ukraine
Labour unions around the world have comdemned Russia's attack on Ukraine and called for an end to the war. A special RadioLabour report.Duration: 11'19"
World's largest
womens' trade union
India's Self-Employed Women's Association is the world's largest independent women's labour union with 2.1 million members. In a webinar organized by the British Trades Union Congress and the International Trade Union Confederation SEWA's Union Co-ordinator, Manali Shah, described the union's history, accomplishments and challenges ahead.Duration: 14'46"
Climate change and
young women unionists
The global union Education International is campaigning to publicise the linkage between women and climate change. Here is an EI webinar focussed on climate change and young women unionists featuring Jo Grady the General Secretary of the University and College Union in the UK.Duration: 7'00"
Maori women fighting discrimination
Maori women have faced discrimination, especially at the workplace, for decades. In a podcast produced by Public Services International three Maori women describe their experiences. The full 34 minute version is on the web page.Duration: 6'11"
Protecting the world's
39 million fishers
Fishers around the world are represented by the International Transport Workers Federation. The ITF Fisheries Campaign has lobbied the Irish government about the conditions of fishers. Comments by the ITF's Fisheries Campaign Lead in Ireland, Michael O'Brien,Duration: 4'50"
Labour supports Palestinian
human rights groups
The Council of Global Unions has condemned the Israeli government for designating six human rights groups in Palestine as terrorist organizations. An interview with Stephen Cotton, the General-Secretary of the International Transport Workers' Federation and current chair of the Council of Global Unions.Duration: 6'22"
Labour unions are
tackling Amazon
around the world
Amazon has 1.3 million employees globally. Labour is trying to help improve their wages and working conditions. An interview with the General Secretary of UNI global union, Christy Hoffman.Duration: 5'48"
Confronting
climate change
in Africa
One of the regions which will be most harshly effected by climate change is Africa with its population of 1.2 billion. Comments by the General-Secretary of ITUC-Africa Kwasi Adu Amankwah.Duration: 6'17"
Pandemic has cost women
$800 billion in lost income
The pandemic has cost women the equvalent of the GDP of 98 countries. Comments by the Director of the International Department of the AFL-CIO in the United States, Cathy Feingold.Duration: 5'37"
How to fight the
war on labour rights
There is a war on labour rights all over the world. The global union industriALL has a four-year action plan to confront the situation. An interview with IndustriALL General Secretary Atle Høie.Duration: 6'29"
New health and safety accord
for Bangladeshi workers
A new health and safety accord for Bangladeshi garment and textile workers has been negotiated by the global unions IndustriALL and UNI. An interview with the Director of IndustriALL's garment and textile department, Christina Hajagos-Clausen.Duration: 5'43"
Five steps to a caring society
Public Services International is part of a group fighting for a five-step programme - the 5Rs - to recognise the social and economic value of care work. An interview with PSI General Secretary Rosa Pavanelli.Duration: 7'56"
Labour lobbies for release
of Julian Assange
Efforts to stop the extradition of Julian Assange to the US intensified after news that the CIA planned to kidnap him. An interview with Tim Dawson who attended Assange extradiction hearings on behalf of the International Federation of JournalistsDuration: 4'46"
Digitalization and labour unions
How labour unions are, and can, use collective bargaining to confront the digitalization of workplaces and public services. Comments by the Assistant General Secretary of Public Services International, Daniel Bertossa.Duration: 7'31"
Labour's plans for
a future of decent work
The global labour movement has a plan for decent work, building equality, reducing informal work, confronting climate change and more. Comments by the former General-Secretary of the International Trade Union Confederation, Sharan Burrow.Duration: 4'41"
Unions fight for
justice in Colombia
Unions in Colombia are fighting for justice for working people / An interview with one of the country's top labour leaders by the Solidarity Centre's Shawna Bader-Blau.Duration: 4'52"
Support for Myanmar unions
Support for unions in Myanmar after the February 2021 coup is growing. Comments by the International Director of the Korean Confederation of Trade Unions, Mikyung Ryu.Duration: 4'43"
Child labour
increases world-wide
The elimination of child labour has stalled. There are now more than 160 million child labourers in the world. Comments by the African Director of Education International Dennis Sinyolo.Duration: 4'42"
Labour tells ILO its priorities
The annual conference of the UN’s International Labour Organization opened in a virtual setting on June 7, 2021. Catelene Passchier, the chairperson of the Workers’ Group at the ILO, outlined labour’s priorities.Duration: 5'14"
Millions losing jobs
in food supply systems
The pandemic is putting the jobs of millions of workers in the world's food supply systems at risk. Comments by the General Secretary of the IUF global union Sue Longley.Duration: 5'28"
Stop the abuses in
Myanmar, Belarus
and the Philippines
The General Secretary of the Building and Wood Workers International global union, Ambet Yuson, told the ILO conference the world must protect democracy and labour rights.Duration: 5'06"
Secretive corporate courts
in free trade deals
Free trade deals often include Investor State Dispute Systems (ISDS) that establish secretive courts to rule on corporate objections to government polices. The UK and Australia are negotiating a trade deal which may include an ISDS. An interview with the Head of International Relations of Unison, Nick Crook.Duration: 8'38"
A curriculum for
the 21st century:
Reading, Writing
and Climate Change
Students need the tools and capabilities to discuss climate change. That is why Education International has launched a campaign called 'Teach for the Planet'. Comments by EI President Susan Hopgood.Duration: 9'41"
Bringing back
public services
from privatization
More governments such as municipalities are taking back previously privatized public services. Comments by the Local and Regional Government Officer of Public Services International, Daria Cibrario.Duration: 12'40"
The effect of
the pandemic
on women
Women have been hit disproportionately harder by the pandemic. Christina McAnea, the General Secretary of Unison in the UK, outlines the solutions.Duration: 6'46"
The abuse of long-term
and elder care workers
UNI Global Union has conducted a major survey of long-term care, nursing home and elder care workers. It shows that many of the workers don't have the equipment they need while working in precarious jobs. Adrian Durtschi, the head of UNI's Care Division says the solutions include public-funding and unionizing the workers.Duration: 9'38"
Uber drivers are
Uber workers
says UK court
The Supreme Court in the UK has ruled that Uber drivers are not independent contractors. They are workers employed by the company so deserve to be compensated as such. An interview with the Legal Director of the International Transport Workers Federation, Ruwan Subasinghe.Duration: 5'48"
Massive job losses
in Australian coal industries
Thousands of workers in the Australian coal sector may start losing their jobs in five years. The global union IndustriALL has produced a report on the transition from fossil fuels. Comments by the National Research Director for the CFMEU union in Australia, Peter Colley.Duration: 7'02"
Workers need more
than just virtual training
Online education can be effective but there is also a need for hands-on training. A presentation about the need for Technical and Vocational Education and Training (TVET) by Education International research coordinator, Martin Henry.Duration: 7'33"
How Africa and the diaspora
are confronting the pandemic
ITUC-Africa and the Global African Worker Institute have produced a series of webinars about how unionists are confronting the COVID-19 pandemic. Comments by ITUC-Africa General-Secretary, Kwasi Adu-Amankwah and the president of America's Coalition of Black Trade Unionists, Terry Melvin.Duration: 5'43"
How social dialogue
has helped countries
during the pandemic
Trade unions have been working with the other social partners - businesses and governments - to help workers during the pandemic. An interview with the Director of the ILO's Workers' Activities Bureau (ACTRAV) Maria Helena André.Duration: 16'45"
Fighting for trade union rights
at Cargill starch plant in Turkey
January 11, 2021 was the 1,000 day anniversary of the firing of 14 workers at the Cargill starch plant in Turkey. An interview with IUF policy officer Burcu Ayan.Duration: 7'08"
Cargill refused plant shutdown
Despite being warned that COVID-19 had entered the Cargill meat processing plant in Alberta Canada management ignored the call by the United Food and Commercial Workers' Union for a plant shutdown. Hundreds were infected and two workers died. An interview with UFCW communications officer Michael Hughes..Duration: 5'28"
Union organising against
the rise of the far right
The British Trades Union Congress has released a report on how unions can respond to the rise of the far right. A presentation by TUC General-Secretary Frances O'Grady.Duration: 10'36"
Workers in Palestine
hoping for decent work
Palestinian workers are hoping for a better future. A UNISON webinar presentation by Assaf Adiv of the Workers’ Advice Centre (WAC-MAAN) in Israel.Duration: 5'05"
Equity and skills development
for workers and labour unions
As the pandemic changes the world of work drastically questions are being raised about equity of access and other issues. A presentation by Education International research coordinator, Martin Henry.Duration: 5'05"
Fighting to re-instate
fired labour leaders in Guinea
The Marriot Sheraton Grand hotel in Conakry, Guinea, fired a workers for accidently breaking a pot of flowers. When union leaders Amadou Diallo and Alhassane Diallo tried to help they too were fired. Interviews with Alhassane Diallo and Massimo Frattini of the IUF Global Union.Duration: 5'10"
The European fight
for water and sanitation
as human rights
Led by the European Federation of Public Service Unions (EPSU) labour organizations in Europe have won a major victory in their campaign to have water and sanitation recognized as human rights. An interview with EPSU spokesperson Pablo Sanchez.Duration: 8'03"
Stopping violence
against transport women
Women who work in the transport sector are often the victims of workplace violence. An interview with the Women Transport Workers and Gender Equality Officer for the International Transport Workers Federation, Jodi Evans.Duration: 7'01"
What COSATU wants
from a Biden administration
The Congress of South African Trade Unions has called on the Biden administration to increase support for multilateralism, help build African economic development, and support Palestine. An interview with COSATU International Secretary Sonia Mabunda-Kaziboni.Duration: 4'37"
Caribbean teachers
confront the pandemic
The pandemic has changed how teachers do their jobs. A report about women teachers in the Caribbean from an online conference moderated by Nadine Malloy (pictured), a former president of the Jamaica Teachers' Federation.Duration: 5'02"
Labour confronts
both the pandemic
and the climate crisis
While the world faces challenges from the pandemic the climate crisis still has to be addressed and a just transition to decent jobs assured. Comments by the Deputy General Secretary of the British Trades Union Congress, Paul Nowak.Duration: 4'47"
Ban nuclear arms now!
The world has enough nuclear material to produce 40,000 bombs. The labour movement is calling for a ban on nuclear arms. Comments by the President of the International Trade Union Confederation, Ayuba Wabba.Duration: 4'44"
Unions are protecting
African teachers and students
The pandemic has hit African teachers and students hard. Unions are working to protect them. Comments by Education International's Chief Regional Coordinator for Africa, Dennis Sinyolo.Duration: 4'41"
Make Amazon Pay
Amazon is taking advantage of the pandemic to dramatically increase its profits while worsening the working conditions of its employees. Comments by UNI General-Secretary Christy Hoffman.Duration: 8'49"
20,000 to lose jobs
in Australian
higher education
In a webinar organized by Education International Matthew McGowan, the General Secretary of the National Tertiary Education Union in Australia – the NTEU - predicts huge job losses amongst employees of higher education due to the pandemic.Duration: 4'43"
Labour calls for
a new social contract
On World Day for Decent Work, 2020, labour called for a new social contract. Comments by former ITUC General Secretary Sharan Burrow and the General Secretary of ITUC Africa, Kofi Adu-Amankwah.Duration: 4'40"
UK labour fights racism
in Britain and the US
At its national conference held virtually September 14-15, 2020, the British Trades Union Congress supported the fight to end systemic racism plus provide decent work and reparations.Duration: 6'55"
COVID-19 should
be declared an
occupational disease
The global unions are calling on governments to declare COVID-19 an occupational disease. An interview with the IUF's Regional Secretary for the Asia Pacific Region, Hidayat Greenfield.Duration: 6'55"
200,000 seafarers
stuck on ships
200,000 seafarers are trapped on ships because of the COVID-19 lockdown. The International Transport Workers' Federation is trying to help. An interview with the ITF's Inspectorate Coordinator Steve Trowsdale.Duration: 7'22"
ILO's ACTRAV helping
East African unions
East Africa has been hit by not only the pandemic but also a plague of locusts and the effects of climate change. The ILO's Workers' Activities Bureau (ACTRAV) is providing assistance to unions in the region. Comments by ACTRAV Director Maria Helena AndréDuration: 7'22"
Solidarity a lesson
of the pandemic
Teachers say lessons about inequality and access to appropriate technology mean no return to normal after the pandemic. Education International General-Secretary, David Edwards, says solidarity is needed and increasing.Duration: 4'39"
Labour opposes WTO
e-commerce agreement
A proposed WTO e-commerce agreement would restrict the rights of governments to regulate on behalf of their citizens. An interview with Georgios Altintzis a Policy Officer in the ITUC's Economic and Social Policy Department.Duration: 8'16"
Canadian union takes on
America's ICE police
The British Columbia Government and Service Employees' Union has used its Shareholder Engagement Programme to object to the relations Thomson Reuters has with America's Immigration and Custom Enforcement (ICE) police. An interview with BCGEU president Stephanie Smith.Duration: 10'30"
Outsourcing worker intelligence with corporate AI and Big Data
Worker intelligence is being outsourced at the workplace by huge corporations using Artificial Intelligence and Big Data. An analysis by Daniel Bertossa of Public Services International and Parminder Jeet Singh (pictured) of IT for Change.Duration: 11'12"
US and Latin American
unions face the pandemic
The American Federation of Teachers organized a webinar to share strategies about how unions can confront the coronavirus. Participants included Fatima da Silva, the General Secretary of CNTE Brazil.Duration: 9'43"
COVID-19 is an
occupational disease
The ITUC is calling on governments to declare COVID-19 an occupational disease. A message from former ITUC General Secretary Sharan Burrow.Duration: 4'42"
Women transport workers deserve decent pay and more respect
The world is realizing that transport workers are critical. But the International Transport Workers Federation says don't forget about the women transport workers. A message from the Chair of the ITF Womens' Committee, Diana Holland.Duration: 5'54"
| 2023-02-06T00:00:00 |
https://www.radiolabour.net/
|
[
{
"date": "2023/02/06",
"position": 34,
"query": "AI labor union"
}
] |
|
$340 Million Anti-Labor Consulting Industry Is Behind ...
|
$340 Million Anti-Labor Consulting Industry Is Behind Contemporary Union-Busting
|
https://truthout.org
|
[
"Tyler Walicek",
"Michael D. Yates",
"Sharon Zhang",
"Marjorie Cohn",
"Lily Meyersohn",
"Anna Claire Vollers",
"Mike Ludwig",
"C.J. Polychroniou",
"Jake Johnson",
"Amy Goodman"
] |
Union-busting firms are teaching corporations to cynically co-opt progressive rhetoric as they crush worker organizing.
|
Honest, paywall-free news is rare. Please support our boldly independent journalism with a donation of any size.
The remarkable spikes in union activity over the last few years have given many on the left cause for hope: could we be on the precipice of a resurgent, newly galvanized U.S. labor movement? In the first three quarters of 2022, the National Labor Relations Board (NLRB) documented a 53 percent increase in organizing petitions — including startling wins by new, independent unions at Starbucks, Amazon, Trader Joe’s, and numerous others, across many sectors. There’s a widespread sense that a qualitative shift has taken place.
That said — despite the perceptible increase in agitation — on quantitative measures, the picture is not quite so rosy. Overall union density in fact declined in 2022, to a new low of 10.1 percent. It’s yet to be seen if newly roused energies will translate into sustained, structured power. By some metrics, much of the present organizing wave seems to have been dashed upon the rocks — in no small part thanks to a merciless backlash from the bosses.
Modernized Union-Busting
In response to the uptick in unionization efforts, corporate bosses have turned to their reliable toolkit of anti-union tactics. The mainstays of management clampdowns — store closures, firings, intimidation, the hiring of replacement workforces (“scabs”) to neutralize strikes, surveillance and illegal manipulation of elections — are just as familiar as they were in the early 20th century, if lighter on club-wielding Pinkertons. (Though the mercenary detectives and picket-line violence are not entirely things of the past.)
Managements, following the advice of their expensive consultants, have found some success in splitting worker solidarity through the cynical application of social justice rhetoric and nebulous progressive values. They may recite the proper ideological shibboleths, but they offer little substantive shop-floor change to match, laundering exploitative practices.
Kim Kelly is an inveterate labor journalist and the author of Fight Like Hell: The Untold History of American Labor. As Kelly put it in an email to Truthout: “Anti-union bosses have been using the same old playbook for centuries, and many of those time-worn tactics haven’t changed — intimidation, retaliation, and misinformation never go out of style. But just as workers and unions have had to adapt to social, political, and technological shifts, so have our enemies in the C-suite.”
These days, companies with an ambiguously liberal aura often conceal anti-union efforts in the trappings of social justice language, diversity and inclusion initiatives, and an ersatz, surface-level social consciousness. An illustrative example is the coffee giant Starbucks, where a rapidly proliferating union campaign has been met with vicious backlash from a corporation that likes to pitch itself as progressive, value-driven and worker-friendly — and tries to capitalize on that image to stanch organizing. Why would employees need a union, the logic goes, when the company already cares so well for them and practically embodies their beliefs and values?
“Starbucks has put itself in a position where it says, and it exudes, that it wants to be better to its partners and its customers while disproving that time and time again, especially with this union drive,” said Gianna Reeve, a Starbucks worker quoted by Candice Bernd in an article for Truthout. So far, the company has put up numerous roadblocks, but has only been able to slow the union’s inexorable march.
These new permutations of anti-union rhetoric make clear that when capital’s priorities are threatened, the boss’s soothing words and insistence on values reliably prove to be little more than window dressing. The bosses, however, did not develop these deceptions on their own.
A Specialized Anti-Worker Industry
Deterring unions in the workplace has become a veritable cottage industry — though perhaps that phrase is inappropriately diminutive for a sector which brings in hundreds of millions annually.
The Labor-Management Reporting and Disclosure Act (LMRDA) offers some rare insight into these operations. The Economic Policy Institute (EPI) estimated that total spending on the union-busting industry amounts to at least $340 million a year. However — because “loopholes in the law’s reporting requirements allow consultants and law firms [to] avoid reporting their work” — a full accounting is currently impossible.
It’s no surprise that the business lobby opposes even this limited disclosure. Corporate interests like the Chamber of Commerce, joined by the American Bar Association (ABA), are seeking to shoot down an Obama-era proposal for a “persuader rule” under the LMRDA, which would require disclosure of funds spent on anti-union consultants who advise management behind the scenes. Experts in legal ethics say that the lobbyist claims of First Amendment violations are unfounded, and that the ABA’s real interest is in protecting a lucrative legal niche.
Legal firms and consultants that specialized in “union avoidance” first swelled in number during the 1970s, as part of the establishment reaction to ‘60s-era sociopolitical turmoil. Research published in the British Journal of Industrial Relations documented only around a hundred anti-union law firms in the 1960s. By the 1980s, there were over a thousand. These boutique consultants, industrial psychologists, and specialist lawyers would come to play a significant role in subduing what was left of the labor movement, and have helped keep U.S. unions pinned down to this day.
Notable law offices include Proskauer Rose, Ogletree Deakins, Jones Day (which also helped Donald Trump attempt to overturn the 2020 election), Morgan Lewis, Littler Mendelson and Ballard Spahr, among others. Such firms field legions of lawyers who are keen to take advantage of all of the loopholes strewn throughout the U.S.’s weak labor laws. Meanwhile, hired agents contracted or supplied by these law offices might advise from the shadows or infiltrate shop floors to sway workers themselves, serving as modern-day strikebreakers who use deflection and confusion in the place of batons and revolvers. They tend to use euphemistic, if still vaguely sinister, terms like “persuaders” or developers of “human capital” to describe themselves.
This work is facilitated by a National Labor Relations Board that is enfeebled by defunding, drained of personnel, and rendered toothless by corporate lobbying and regulatory capture. More broadly, the anti-union industry works in an environment in which legal protections for labor have been throttled — both under the reactionary Trump administration, the professedly “union-friendly” Biden, and many presidents past.
The result has been that U.S. workers cling to workplace rights that, relative to other “developed” countries, are weaker by orders of magnitude. It’s the inevitable result of the decimation of union power, while lopsided legal advantages and political barriers loom large. Precedents like 2018’s Janus v. AFSCME, which bans public-sector unions from collecting dues from nonunion employees, and a Supreme Court stuffed full of right-wing justices promise to further disempower workers.
While the anti-union consortium is not a monolith, there is a great deal of collaboration. Upper-class solidarity runs deep — the elite and their partisans understand very clearly where their interests lie, and collaboration can be as frequent as competition. From the nation’s lavishly funded networks of right-wing foundations, think tanks and astroturfed “activist” groups have come ideological “anti-union organizers” — like those of the Koch-backed Freedom Foundation, which canvasses West Coast union members, harassing them to cancel their memberships.
More typical, though, is mundane business networking. Today, corporate managers attend full-blown conferences on union deterrence, like the one hosted by the Council for a Union-Free Environment (CUE), which calls itself a “non-profit, member-led community [of over 200 businesses] with the latest techniques for improving labor and employee relations.”
The Intercept managed to get a glimpse inside the CUE conference, where corporate managers receive updated information on legal loopholes, political advantages, strikebreaking techniques and winning union-busting strategies. A Kellogg’s vice president could reportedly be heard describing union negotiators as “behaving more like terrorists than partners.”
Tellingly, nowhere on CUE’s website is the meaning of their acronym spelled out; instead, they only describe themselves as an “Organization For Positive Employee Relations.” Again, euphemisms abound. This industry is obliged to disguise its true nature so as to better infiltrate and influence. Ever rebranding, anti-union operatives can be expected to find new means of bureaucratic and rhetorical camouflage.
Union-Busting’s Time-Honored Traditions
The bosses’ tactics range from crude to complex — though it’s often the case that the simplest tools remain the most effective. Some strategies date back practically to the dawn of the Industrial Revolution, despite federal labor laws that are theoretically intended to level the playing field. All too often, the barriers between legal and illegal practices are porous. U.S. employers “are charged with violating federal law in 41.5 percent of all union election campaigns,” according to EPI data. The National Labor Relations Act (NLRA) of 1935, also known as the Wagner Act, protects private-sector collective bargaining rights. Yet employers encroach on those rights as a matter of course. Firings, demotions, loss of benefits, workplace closures (or threats thereof), interrogation about union activity, surveillance, refusing to hire union members — all are NLRA violations.
According to EPI data, unfair labor practice (ULP) charges of coercion or illegal discipline were filed in 29 percent of all elections surveyed; larger companies — those with more than 60 employees — were charged with violations in 54.4 percent of elections. The real rate of unreported violations is doubtless far higher. Employers are able to manipulate NLRB investigations with stalling tactics, and the NLRA does not ban all possible coercive measures. An analysis by the EPI and Cornell University researchers estimated that, “whereas 30 percent to 40 percent of elections had a ULP charge filed with the NLRB, a detailed survey revealed that unions claimed employers committed ULPs in 89 percent of elections.” (That analysis dates to 2009, but updated EPI research corroborated comparable figures up through 2018.) “One out of five union election campaigns,” reports the EPI, “involves a charge that a worker was illegally fired for union activity.”
Ongoing Conflicts, Historic Developments
The union drive at Starbucks has been one of the most visible and protracted of last year. Since their first successful election at a location in Buffalo, New York, the independent Starbucks Workers United had, as of December 2022, organized a stunning 267 stores, winning around 80 percent of elections held.
Public relations blitzes by top Starbucks executives and CEO Howard Schultz about the company’s progressive values and “inclusive” working environment are contradicted by its unfavorable working conditions and a retaliatory anti-union campaign. Outright store closures with deeply suspicious timing have been a common occurrence. Captive audience meetings, firings, intimidation, and other strong-arm tactics have been employed against pro-union workers.
By the end of 2022, Starbucks had been hit with a staggering 548 ULP charges. Federal officials described the violations as “substantial.” It’s instructive to consider how quick management was to hold gender-affirming health care for trans employees hostage — treating marginalized workers’ health as little more than a bargaining chip. As Schultz professed good faith from one side of his mouth, the other was ordering that new raises and benefits be denied only to union members.
A similar situation arose at Amazon, which has lashed out mercilessly at the slightest hint of organizing. Scattered organizing efforts of past years were quickly crushed, but a 2021 union drive at an Amazon warehouse in Bessemer, Alabama, by the Retail, Wholesale and Department Store Union (RWDSU) nearly met with success, although it was ultimately stymied. Yet Bessemer was only a prelude: In April 2022, the independent, newly formed Amazon Labor Union (ALU) won their election at a Staten Island facility; widely greeted as a triumph, the effort propelled organizer Chris Smalls and the ALU to the national stage.
This story is by now a familiar one, though no less inspirational for it. What may be less known are the true lengths to which the megacorporation has gone in its scramble to protect profit. As Kim Kelly pointed out in an email to Truthout, one tactic is “the increase in surveillance on the clock and otherwise. Digital communications [make it] that much easier for the hierarchy to observe the behavior of its lower ranks.”
The Bessemer effort was met with strong-arming and overreach that extended into outright cheating, as determined by the NLRB. The company unveiled “a sophisticated campaign that involved sending text messages and mailers to employees warning them of the downfalls of a union, offering bonuses to employees who quit before the union election, and even allegedly accessing the drop box that employees used to mail their ballots,” as Julia Rock reported for Jacobin.
Amazon has also employed professional for-hire strikebreakers, the infamous Pinkertons, to conduct anti-union spying and infiltration. And last summer, The Intercept publicized Amazon plans for an internal messaging app that would ban the word “union,” “restrooms,” “slavery,” and other revealing terms. The list goes on; Amazon has fielded anti-union “intelligence analysts,” factory-floor infiltrators, good-cop/bad-cop ploys against workers, and systematic espionage against unions, activists, and more.
Amazon and Starbucks are only two of the more prominent examples of such struggles. A planned work stoppage by railroad unions over the denial of sick leave to overburdened railway employees was broken when President Biden signed legislation forbidding the strike. The coal workers’ strike at Warrior Met, on which Kelly has reported thoroughly, has been ongoing since April 2021; it’s been marked by picket-line violence, police crackdowns on strikers, and an intransigent management.
Other corporations have turned to the legal complex, like the notoriously anti-union Tesla; Google, which appears to be at the end of its tolerance for employee dissatisfaction; and Apple, which has hired legal outfit Littler Mendelson and faces ULP charges for interrogation and surveillance. Media workers have not been exempt: Jones Day has been the go-to legal firm for media outlets attempting to thwart union efforts. Columbia Journalism Review reported on an invite-only, Jones Day-hosted anti-labor conference, “where media outlets in the room included The New York Times, The Washington Post, Slate, Univision, and Atlantic Media.”
Universities — however keen the right is to portray them as hotbeds of radicalism — are no different. Modern U.S. colleges are profit-seeking enterprises, with massive endowments, investment portfolios and real estate holdings. Accordingly, a spate of organizing among low-paid graduate students and adjunct faculty was not welcome news to administrations. In one of many examples, the University of Pittsburgh spent $2 million on an anti-union law firm to deter unionization efforts.
Union-busting efforts distort and co-opt progressive language to defend not the working class or the marginalized, but power structures and the status quo. One facet of this approach is the “Employee Resource Group” (ERG) — an employer-controlled venue for collectivity without collective bargaining. Dissent is funneled into these internal pseudo-unions, which allow for a watchful eye over the workforce and diffuse tempers, without employers ceding any power. The Intercept cited figures from consultant firm McKinsey & Co.: a survey of “423 organizations employing 12 million people” found a dramatic post-pandemic increase — “close to 35 percent of firms have added or expanded ERGs since 2020.”
The ERG harkens back to the days of the “company union,” which served a similar function in defanging resistance. Company unions were banned by the Wagner Act, and there’s a good argument to be made that modern ERGs are in violation, a company union in all but name. They are now a common feature of large workforces, with some expressly designed for workers from marginalized groups. Groups for marginalized employees might allow workers to vent frustrations, but the managers will be sure to steer them away from collective action or material change. Employees might find solace or solidarity, but their energies will be directed away from unionization.
Kelly remarked on the dissonance: “Whether it’s a ‘consultant’ pausing to make a land acknowledgement before unspooling another line of anti-union bullshit” — the case of REI comes to mind — “or a boss trying to convince their workers that unions are corrupt, money-hungry havens for racist, conservative old white men, [they] seem to have learned that by using twisted analyses of race and class — or embracing performative, hollow ‘wokeness,’ for lack of a less grating word — they might be able to trick workers.”
A Full-Bore Crackdown at Trader Joe’s
The popular grocery chain Trader Joe’s has likewise faced its first union drives. Just as in the case of Amazon, Starbucks, and now Peet’s Coffee (which just last month saw its first unionized store, directly inspired and assisted by Starbucks union members), Trader Joe’s workers have formed an independent union — i.e., one specifically for that company’s employees. Organizing began in response to pandemic hazards, but it wasn’t until the summer of 2022 that Trader Joe’s United (TJU) successfully unionized a store. After that initial win in Hadley, Massachusetts, other locations soon followed, as management rushed to stem the rising tide.
Truthout spoke with a union organizer at a high-volume Trader Joe’s location in a major market who requested anonymity in order to avoid inviting further retaliation from management.
This organizer and her in-store allies, in coordination with external TJU members who advised them, were central players in the union drive — to which management reacted with, as she described it, “a shock-and-awe anti-union campaign.” Her story of her experience at the receiving end of a coordinated, professional crackdown is illustrative, and harrowing.
First, an ominous nighttime message from a manager and a note posted in the breakroom “inspired anxiety.” The following day, managers “fired one of our lead organizers,” a Black woman, citing unconvincing justifications. “That really scared a lot of people of color in the store, especially Black people, who had already been worried about retaliation and firings,” the organizer said.
The fired employee was an experienced and well-liked organizer. Her loss impacted the campaign “not only because of the implications for the racial aspects/dynamics of our drive,” continued the source, but also because “she was a powerful pro-union presence” who “made others want to get involved and showed them the power of unions and worker solidarity.”
This and other pre-campaign firings left the most visible employee organizers as a largely white group, leading to some hesitancy from workers of color. The source believes this was carefully calculated. Management identified divisions and “exploit[ed] them in a savvy way to undermine trust in the union,” she remarked. “They were saying, ‘These are white people speaking on these racial issues. Are you comfortable with that?’”
Captive audience meetings were held, and managers pulled union supporters into individual one-on-one “ambushes.” The climate of mistrust and division that the bosses conjured destabilized the organizing effort, and ultimately, the union lost at the ballot box by 14 votes. The organizer underscored how thoroughly she felt that management had weaponized social justice rhetoric.
“Our [manager] is a woman of color,” she went on, and other bosses leapt to claim “how much [the union] hurt her feelings.… A critique [of] managers, to some workers, feels like a personal attack.” That empathy was manipulated to vilify the union organizers. “The message was, ‘You are accusing people of being racist,’ rather than, ‘You are pointing out a pattern of targeted harassment.’” Management’s canny rhetoric inverted the organizers’ narrative. “You can imagine,” she continued, “in a very racially diverse group, how much voltage these racial issues have when they’re not handled in the most sensitive or democratic way.”
The barely concealed subtext was, “‘You’re destroying this workplace,’ ‘You don’t care about the workers,’ etc. — pointed at the union.”
“It’s a psychological onslaught that’s hard to describe unless you’ve been through it,” the organizer shared. “The heart of the anti-union campaign was to sow enough doubt about the truth and who you can trust that makes it really psychologically challenging to advocate, not only as an organizer — because you’re trying to present a trustworthy and solid operation to your coworkers so they’ll want to vote for you — but also as an individual.”
This organizer’s account drove home how emotionally grueling it can be to look down the barrel of a campaign designed by expert manipulators. High-level psychological operations conducted from far above impose confusion and frustration, negating solidarity and rendering certainties uncertain. Despite the taxing setback, she underscored that this struggle is far from over: the union did win 60 votes, and ULP charges are pending. Meanwhile, they’ve found hope in the fact that a third Trader Joe’s just unionized in Louisville, Kentucky. Whatever the odds, it should be remembered that, even in the wake of a loss, committed union organizers rarely yield entirely — rather, they regroup to fight another day.
A History Still Unwritten
As devastating as corporate interference can be, the appearance of unions at places like Starbucks and Amazon was, until very recently, considered almost unthinkable. Organizers have also started exposing some of management’s more devious tactics — part of their pushback against Amazon’s anti-union shop floor agents was to “compile unflattering dossiers, to show workers that the consultants get rich ‘convincing poor people to stay poor,’” said ALU leader Connor Spence, quoted in HuffPost. “We turned the internal systems against [Amazon] in ways even some managers wouldn’t know how to do.”
Militancy carries its own momentum: it’s notable that the spate of successful union efforts at Starbucks didn’t just inspire workers at the similar Peet’s Coffee — they collaborated directly. The dissemination of knowledge, and the assiduous increase in positive examples, will help to armor future efforts and allow unions to gain crucial footholds before employers can open their coffers to union-busting operations. “Inoculation is everything,” Kelly added. “It’s absolutely critical to head off the bosses’ bullshit at the pass, and to prevent them from gaining any opportunity to plant seeds of doubt.”
Still, Kelly voiced concerns that are shared by many on the left: “I am worried that if the capitalist goons at Amazon and Starbucks both really start working overtime to crush the Amazon Labor Union and Starbucks Workers United (which they’ve already been doing, with relish) that it may have a cooling effect on the amount of energy and enthusiasm we’ve seen spring up in the wake of those wonderful victories.”
But the struggles of recent years will continue to reverberate. Regardless of the future tactics that might issue forth from managements and their well-paid legions of anti-union consultants, the stunning upsets at behemoths like Starbucks and Amazon are now an indelible part of the story of U.S. labor. Kelly spoke for many others when she told Truthout: “I’m so proud and awed by the incredible amount of work these workers have put in and the history they’ve made.”
Urgent appeal for your support: 10 Days Left With Trump’s fascist agenda driving the narrative, it’s the duty of independent media to disrupt corporate propaganda. Yet, at such a pivotal moment, donations to Truthout have been declining. Why? Blatant political censorship from Big Tech. As we face mounting repression, Truthout appeals for your support. Please donate during our fundraiser — we have 10 days left to raise $50,000.
Copyright © Truthout. May not be reprinted without permission.
| 2023-02-06T00:00:00 |
2023/02/06
|
https://truthout.org/articles/340-million-anti-labor-consulting-industry-is-behind-contemporary-union-busting/
|
[
{
"date": "2023/02/06",
"position": 75,
"query": "AI labor union"
}
] |
Why Laurel Exists
|
https://www.laurel.ai
|
[] |
We started the company six years ago to empower +1B knowledge workers to produce twice as much value in half the time. ... AI is the tailwind we must take ...
|
On February 1st, we said goodbye to Time by Ping and introduced the world to Laurel.
Today, I want to tell you about the biggest driving force behind that change – our raison d'être.
Our Mission
Our mission is—and always will be—to return time.
Knowledge workers (people who make money with their minds) spend an average of 9 hours a day working but only spend 3 hours adding value. We started Time by Ping six years ago to empower these +1B knowledge workers to produce twice as much value in half the time.
Ambitious to say the least, but it has been done once before.
In December 1913, Henry Ford installed the first assembly line for an automobile. This reduced the time it took to produce a car from 12 hours to 1.5 hours (an 88% decrease). The productivity gain enabled Ford to reduce the average work day from 14 hours to 8, while simultaneously doubling wages. Asking people to work less and make more was seen as an ensured failure mode for the car company. Instead, their profitability doubled within 2 years, and Ford is now widely credited for creating the middle class in America.
The next platform shift will be AI.
Models, like OpenAI’s GPT-3, have indexed the entire Internet to learn how humans speak. We are fast approaching a point where human or machine-generated text will be indistinguishable. But despite all the buzz ChatGPT has generated recently (all of it well deserved), we agree with Chamath Palihapitiya’s take on E106 of All-In:
"But when we get there, all of these models as a service will be very much commoditized. And I think the real value is finding non-obvious sources of data that feed it … the real key is where do you find proprietary sources of data that you can learn on top of? That's the real arms race. … Those are the kinds of moves in business that we will see in the next 5 to 10 years that I find much more exciting and trying to figure out how to play in that space. But I do think that ChatGPT is a wonderful example to point us in that direction. But I'm sort of more of that case, which is, it's a cute toy. But we haven't yet cracked the 1 to 2% of use cases that make it super useful."
Laurel is a data company that uses timekeeping as a way to collect work as it is happening. No one else has this data, and no one else has a path to get it.
When we set the mission, we didn’t know how we would achieve it. Just that we would either (i) fail (spectacularly) or (ii) get lucky. Airbnb took advantage of the 2008 housing crisis. Google benefited greatly from the burst of the dot com bubble. AI is the tailwind we must take advantage of.
Phases of Time Exploration
With the advancements in AI, machines are now better positioned than humans to take inventory of time. Our first product leverages machine learning and automation design to shift the burden of keeping time from human to machine.
While other timekeeping companies are aimed at making it easier for humans to keep time, our intent is to make machines do time on behalf of the human.
From a data lens, this allows us to measure what people do—not what people say they did—giving us the inputs to accurately measure cost.
With cost inputs that are accurate and aggregated, we will ensure buyers of services can stop buying the input of time and start buying the output of value. After all, in a factory model, an hour can only be worth an hour of time (there are only so many widgets you can push in an assembly line). In the knowledge economy, the value of one hour has no upper bound. In doing this, we will flip the incentive model of 20% of US GDP.
Phase 3 is then taking the work data that only we have access to and using it to automate the 58 percent of time knowledge workers spend on manual and repetitive tasks. This will allow humans to apply the 4-5 hours a day we are able to focus on creative pursuits and problems that machines are decades away from being able to compete with us.
The best companies convince the world they were something they didn’t previously realize.
Nike made us believe we were all athletes.
Apple showed us we were all creators.
Shopify convinced us we were all entrepreneurs.
We do not exist to make timekeeping easy. We do not even exist to make timekeeping irrelevant.
We exist to make 1 billion people leverage their time.
Welcome to Laurel.
| 2023-02-06T00:00:00 |
https://www.laurel.ai/resources-post/why-laurel-exists
|
[
{
"date": "2023/02/06",
"position": 81,
"query": "AI workers"
}
] |
||
Upskilling: How to Win the Battle for Data + AI Talent
|
Upskilling: How to Win the Battle for Data + AI Talent
|
https://pages.dataiku.com
|
[] |
Teams need a common AI/ML platform that ensures workers of all skill levels — from business analysts to graduate-level data scientists — want to use it. 2. No ...
|
The top two blockers for scaling AI are hiring people with AI skills and identifying good business cases.
To address both issues at once, build teams made up of both data and domain experts, plus evolve the operating model for AI initiatives over time. This ebook demonstrates how to execute on this winning combination.
| 2023-02-06T00:00:00 |
https://pages.dataiku.com/battle-data-ai-talent
|
[
{
"date": "2023/02/06",
"position": 87,
"query": "AI workers"
}
] |
|
How Must Journalists and Journalism View Generative AI?
|
How Must Journalists and Journalism View Generative AI?
|
https://www.scu.edu
|
[
"Santa Clara University"
] |
In conclusion, should the news media industry use generative AI for journalistic writing? The short answer: No. There is too much ethical debt these systems are ...
|
Subramaniam Vincent
Subramaniam Vincent (@subbuvincent) is the director of journalism & media ethics at the Markkula Center for Applied Ethics at Santa Clara University. Views are his own.
How might journalists–reporters, illustrators, podcasters, broadcasts, editors, data journalists, investigators, and documentary filmmakers–view generative AI? This is a complex topic that touches on many aspects. A brief article cannot be comprehensive on all of the complexities lurking behind this question. I’m going to focus on the question of whether the news media industry should use Generative AI for journalistic writing. Journalists use tools all the time for their work, so the means and ends lens may be a practical way to sort through the ethical questions.
Let’s start with ‘ends’
By “ends,” I mean efficiency for journalistic writing. Let’s say we were not concerned with how ethical generative AI is as a technological means to use for journalism writing. We simply said, it’s already here, it’s a competitive marketplace, and there’s always economic pressure. Let’s just use it for journalistic news writing. Here are the considerations.
Journalists, at least normatively, engage in truth determination as a key function. The everyday practice of reporting the news is rooted in the journalistic agency of covering reality. Journalistic writing is a specific type of writing–its north star is the truth, as elusive as that becomes. (Of course, there are massive failings in journalism–truthful narratives do not always emerge as selective subordination of voices, people, facts, and stories have a long-running history in hegemonic journalistic practice.) But fundamentally, the professional and the practice can, at least in principle, be questioned around truthfulness as a standard.
Now let’s look at the case of using ChatGPT to write.
Truth and generative AI
Truth is not the goal. OpenAI is open enough to say that there is no source of truth in ChatGPT. See their limitations section.
“ChatGPT sometimes writes plausible-sounding but incorrect or nonsensical answers. Fixing this issue is challenging, as: (1) during RL training, there’s currently no source of truth; (2) training the model to be more cautious causes it to decline questions that it can answer correctly; and (3) supervised training misleads the model because the ideal answer depends on what the model knows, rather than what the human demonstrator knows.”
Go further. Ask OpenAI’s playground itself on whether the machine can tell the difference between truth and fiction:
“GPT-3 and ChatGPT do not have a ground truth reference, so they cannot tell the difference between truth and fiction. However, GPT-3 and ChatGPT are trained on a large corpus of text, which can help them make informed guesses about the plausibility of a given statement.”
It’s in the design. ChatGPT (or competitors who also use large language models or LLMs) is not designed to operate anchored to the word “truth” in a realistic or even discursive sense of the term. To be clear, what is ChatGPT for? In small font, at the bottom of the ChatGPT page, you’ll see this:
“Our goal is to make AI systems more natural and safe to interact with.”
There is a date-cut off. If you push ChatGPT hard enough about current developments, it will repeat one line back to you–that its training cut-off date is 2021. Try asking ChatGPT, “Did Kari Lake win in Arizona” and you’ll see what I mean. Since that election happened in 2022, ChatGPT does not “know” about it. No training data.
So even from a strictly exploitative and extractive ends perspective, ChatGPT is not for journalistic writing.
Trusting generative AI for stories
Enough trust discussions already. I’ve written before that the trust problem in mainline journalism is more complicated than the elite narrative has made it out to be. See these two pieces for more: (Values, not trust, and What Is Our Brain Doing When We Click News Articles?)
Someone tested generative AI news headlines with people. Foretelling how the public at large may treat generative AI news writing was some research that came out in mid-2022, about six months before OpenAI released ChatGPT. In their work studying how people will perceive news generated by AI, a group of researchers (Chiara Longoni, Audrey Fradkin, Luca Cian, and Gordon Pennycook) pointed out that if it is disclosed that a headline was AI-generated (a form of labeling), they find that readers attach an additional credibility deficit to the news. See: News from Generative Artificial Intelligence Is Believed Less.
Generative AI is no magic bullet. If journalists start using generative AI for news writing, the so-called trust deficit may get another wheel to accelerate on.
Will AI labels/transparency work? Doesn’t transparency demand that news organizations using machines to write stories should disclose that to users? This finding only brings up a tension between the risk of labeling and the assumptions of the reader. It may only further drive publishers to be resistant to label AI-generated news text as such.
Binary disclosure won’t cut it. The real question for news readers and publishers is not plain disclosure in a binary sense: Written by human vs. written by generative AI. Transparency has to be along AI-literacy lines among the public, beyond simplistic labels. We may need a deep transparency of models, training data corpora, and model limitations to the reader, in plain de-complexed language. That is a hard ask.
The ‘means’ question with Generative AI
‘Means’ matter for ethical journalism. The deep transparency question is a serious one. Like, how does generative AI work and what does it have to do with how journalism is put together? Here, things get even more ethically complicated.
AI opacity means sourcing is a deadend. ChatGPT does not cite all its sources when it generates text. This is how its (large language) models work. For journalists, sources, and sourcing always matter. OpenAI has not posted a list of all their training sources for ChatGPT. There are some guesses floating around. So why trust a talking tool that is opaque?
Appropriating the open web. Further, there are substantive ethical questions about crawling the open web and using the creative expression of humanity (even if all the text was uncopyrighted) this way for generative machines. It’s one thing for the collective commons to be open to humanity. It’s another thing for it to be used for massive computational pattern-matching models to get machines to blindly mimic humanity. And it comes as no surprise, for example, when Getty Images sued Stability AI (image generative AI) for copyright infringement in London.
In this interview published by the Tech Policy Press on an indigenous perspective on generative AI, Michael Running Wolf (North Cheyenne man, computer science PhD student, and former Amazon engineer) says this:
“It’s a lie to say that it only costs electricity to generate the art. That’s a lie. These Stable Diffusion could not do this if they didn’t have the ability to scan the intellectual property of the internet. And that is worth something.”
Compare generative AI to a child learning language in the open world. Training a machine is not the same as ChatGPT going from kindergarten to college in a city and coming out like a grown-up with communicative abilities. For journalism, the “means” question then is this: How a generative AI’s training data corpora were put together and the extractive norms that went into it–must matter to whether you might consider using it for any inputs to a story.
Risks. There is the risk of perpetuating cultural appropriation and unremunerated creativity through everyday media work. There’s already the admitted risk of human culture’s historical and current power biases around people, social groups, gender, and roles that will simply show up in the text. How much will an editor be able to catch? There are ethical questions about Large Language Models upstream of journalism that are unresolved and currently in serious debate.
Two great interviews on the generative AI hype for journalists.
One area of Generative AI that has potential for journalism is summarization
Why is summarization a useful intervention area? On many occasions, breaking news and enterprise reporters are criticized for not including enough context in a story. Context can come in the form of summarizing the past on the same issue, or a key question on a development, or writing up a chronology, etc.
Enter search engine summarizer combos. There are some new search engine companies emerging that combine the convenience of conversational-AI with the traditional model of search engine results ranked by some measure of authoritativeness, reputation, relevance to queries, etc. Try this on the search engine Neeva.com:
“BLM response to Tyre Nichols murder by police.”
See the screenshot below. (Note, you will need an account for the generated AI summary above the search results).
Summarizers with citations are intriguing. On the face of it, Neeva claims to be generating their summary responses to queries using the citations they link to below the summary. It is helpful to know which citations were used by the machine to produce this summary.
How does that help journalism? If a journalist were looking to quickly come up to speed on various aspects of an issue that was receiving wide coverage, she could check the cited links to learn more and then review the summary.
Cheap context generation. So it may seem that there is a case for search engines with a conversational interface being used as a source of cheap context generation (means) that reporters can insert into story sidebars (ends). And reporters can insert these with full credit to the search engine and the upstream citations.
Still, no wishing away the ethics of LLMs yet. Neeva also notes it uses LLMs, so all of the AI ethics questions about LLMs upstream of journalistic use still exist.
But from an “ends”-only standpoint, one distinction, however, is that search engines in principle can be held to an expectation that they do not serve fiction in their results when queried about current affairs, and hence their summarization ought to be held to those basic standards. ChatGPT on the other hand is open about not being able to distinguish between fact and fiction, a distinction in design.
In conclusion, should the news media industry use generative AI for journalistic writing? The short answer: No. There is too much ethical debt these systems are creating upstream before the tools even reach journalists. You may have editors review the generated text for facts and accuracy, but regressive biases in categorization and characterizations will be harder to catch. If you are summarizing historical contexts into a piece, and want to try machine summarizers, run them on selected articles and documents you yourself have vetted first. Proceed with caution.
| 2023-02-06T00:00:00 |
https://www.scu.edu/ethics-spotlight/generative-ai-ethics/how-must-journalists-and-journalism-view-generative-ai-/
|
[
{
"date": "2023/02/06",
"position": 3,
"query": "AI journalism"
}
] |
|
ChatGPT's impact on the media landscape
|
ChatGPT's impact on the media landscape: navigating the future of AI and journalism — Verde Brand Communications
|
https://www.verdepr.com
|
[
"Matt Sklar"
] |
Discover the impact of ChatGPT, the AI tool created by OpenAI, on the media industry and how it is changing the game for journalism, writers, and consumers.
|
Is AI content immoral?
The morality of AI content is a complex and debated topic. Some people argue that AI-generated content, such as fake news, can be harmful and immoral because it misleads people and undermines trust in information sources. Others argue that AI-generated content is just a tool and that it is the responsibility of users to verify the information and use it ethically.
Ultimately, the morality of AI content depends on how it is used and the intent of those who use it. It is important for individuals and organizations to be aware of the potential risks and to use AI-generated content responsibly, in a manner that aligns with ethical and moral principles.
Our take:
It is only a matter of time before people figure out how to weaponize new technologies (and make money off of it) and steal the work of writers, authors, artists, coders, and more; the need for regulation is very apparent.
In summary:
While this new technology is going to revolutionize the way people interact with the internet and each other, we see this as an opportunity to create compelling stories, refocusing our brands, products and staff to relentlessly focus on a customer.
Modeling is pointing towards an algorithm which acts like a ski shop or running shoe store employee: When a person walks into a store to by a pair of shoes or skis/snowboard, the employee starts asking specific questions such as, where do you ski, what kind of terrain, what ability level, what’s your budget, and so on, to ensure they can recommend the best product for you. Does your brand have that information on your website? Do media outlets have that information?
Providing the media with product specifications, and going beyond that by explaining the target audience and purpose of the product will resonate with both your customers and the media. These types of stories will win the ‘hearts and minds’ of the robot, too.
Example: 22/23 Rossignol Sender 106 Ti Plus by Blister>
In addition, uplifting people and stories is irreplaceable by robots (for now), an example of this is how Verde is Making News with Ambassadors. Creating experiences for consumers, brands, and media to come together can help facilitate those stories as we do with Launch Dispatch and our media experiential events, which will continue to evolve to meet the needs of our clients and consumers.
Marketers and media need to be careful, thorough, and continue to create original and trustful content that is highly relevant to a specific audience.
As Mark Schaefer said - may the most human company wins.
Please contact us at Verde to tell your story.
A portion of the blog was generated by OpenAI’s ChatGPT.
| 2023-02-03T00:00:00 |
2023/02/03
|
https://www.verdepr.com/blog/2023/2/3/ai-chatgpts-impact-on-media-landscape
|
[
{
"date": "2023/02/06",
"position": 4,
"query": "AI journalism"
}
] |
Top 10 AI Tools for Journalists to Boost Writing Speed and ...
|
Top 10 AI Tools for Journalists to Boost Writing Speed and Quality
|
https://influencermarketinghub.com
|
[
"Geri Mileva",
"About The Author",
"An Experienced Ip Network Engineer",
"Distinguished Writer At Influencer Marketing Hub",
"Specializes In The Realms Of The Creator Economy",
"Ai",
"Blockchain",
"The Metaverse. Her Articles",
"Featured In The Huffington Post",
"Ravishly"
] |
Some of the best AI tools for journalists that we've found include Jasper, Connexun, LongShot, Pinpoint, and JECT.AI. Can AI tools ...
|
Enter AI tools for journalists—a game-changing development that’s transforming newsrooms worldwide. These cutting-edge technologies offer journalists innovative solutions to streamline their workflows, enhance accuracy, and uncover stories hidden within vast amounts of data. From writing and fact-checking to data analysis and content generation, AI tools are reshaping the future of journalism.
The use of AI tools for journalists can be viewed as a further support tool. These enable you to quickly access new information, automate repetitive tasks, uncover emerging trends, and analyze large volumes of data, among other capabilities. Find out which tools you can use to streamline how you write the news.
Top 10 AI Tools for Journalists to Boost Writing Speed and Quality:
Top ai tools for journalists 2025 1. Jasper.ai Jasper AI (formerly Jarvis) is a powerful and versatile AI Content Generator to help streamline your workflows. With Jasper, you can generate social media content, advertising copy, emails, and SEO-optimized articles up to 10 times faster. Furthermore, it lets you write—and read—content in as many as 25 languages, including English, Japanese, and Spanish. Jasper is loaded with features that will help journalists write more efficiently. Some of the noteworthy picks include Creative Story, which assists you in writing creative stories. Content Improver, a feature that optimizes your content to make it more engaging and Engaging Questions, a feature that lets you ask clever questions to your audience to drive engagement. Despite its wealth of features, Pattern Recognition is one of this AI writing tool’s best features. Jasper identifies your writing pattern to generate content that has a similar writing style to yours. Plus, it’s trained on an expansive array of data points. It browses the entire web, ensuring that while your output matches your writing pattern, it doesn’t replicate anything already available on the internet. So far, Jasper has been able to write over one billion words. Some of the world’s biggest names use it, including Google, HarperCollins, and IBM. Key features Long-form editor
Pattern recognition
Plagiarism detector
Enables real-time collaboration
Templates for 50+ use cases
Integration with Surfer SEO Pricing Billed annually, plans cost the following. Note that costs will vary depending on how many words you write per month: Creator – approximately $39 per month (billed annually)
approximately $39 per month (billed annually) Pro – approx. $59 per month (billed annually)
approx. $59 per month (billed annually) Business – contact Jasper representatives for pricing details 2. Pinpoint Pinpoint is part of Google’s Journalist Studio, a suite of different tools, which includes a fact check explorer, data visualizer, and real-time content insights that enable journalists to work more efficiently and securely. Pinpoint leverages the capabilities of Google Search, AI, and machine learning to help journalists write and research material for breaking news, investigative stories, and more. It lets you upload and analyze a large volume of documents, up to 200,000 copies of different file types and sizes for each collection, extracting key entities. It also allows you to share documents and collaborate with other journalists. The Hearst Media Group, The Boston Globe, and Verificado have used pinpoint. Key features Lets users transcribe audio files
Analyzes a range of documents, including handwritten ones
Industry-leading privacy and security
Lets you organize documents using custom labels Pricing Free to use for both read-only and full access. To get full access, you may request for one here. 3. QuillBot QuillBot is an AI paraphrasing tool that lets journalists rephrase any text while ensuring that your content retains the correct vocabulary, tone, and style. Additionally, it has a grammar checker, plagiarism checker, and summarizer. The AI writing tool is customizable, allowing you to determine how much of your vocabulary you want to change. You also get access to a list of synonyms thanks to an AI-powered thesaurus. QuillBot has seven paraphrasing modes: Standard – Balances the input text with the paraphrased output to retain the original’s meaning
– Balances the input text with the paraphrased output to retain the original’s meaning Formal – Paraphrases text to make them more professional and sophisticated
Paraphrases text to make them more professional and sophisticated Creative – Transforms original text into passages that are more expressive and inventive
Transforms original text into passages that are more expressive and inventive Shorten – Can be used if you’re aiming for conciseness or clarity
– Can be used if you’re aiming for conciseness or clarity Fluency – Helps you improve your language and eliminate grammatical errors
Helps you improve your language and eliminate grammatical errors Simple – Lets you generate paraphrased text that is simple and easy to understand
Lets you generate paraphrased text that is simple and easy to understand Expand – Gives more detail and depth to the generated text It integrates with many of the writing tools that writers are already using, such as Microsoft Word and Google Docs. You can also add it as a Chrome browser extension. Key features Easy to use
Can be used for four English dialects: US, UK, CA, and AU Pricing Free – limited to 125 words
limited to 125 words Premium – contact representatives for pricing details 4. Connexun Get real-time access to multilingual headlines, articles, and summaries with Connexun, a news and text analysis API tool. Connexun uses B.I.R.B.A.L (Brilliant Information Research Big-Data Algorithm), its proprietary AI engine capable of applying natural language processing (NLP), machine learning classification, and interlanguage clustering to filter information for different users and needs. B.I.R.B.AL. is capable of aggregating news, as well as classify and summarizing content. Using Connexun, journalists can track news in real-time, gain strategic insights through AI-driven media intelligence, conduct market research, and perform financial analysis. Key features Enables media and web monitoring
Reputation detection capabilities Pricing News API – Basic: $9.99 per month, Developer: $19.99 per month, Pro: $29.99 per month, and Custom pricing
Basic: $9.99 per month, Developer: $19.99 per month, Pro: $29.99 per month, and Custom pricing Text Analysis API: Contact Connexun for more information 5. LongShot AI LongShot AI is a long-form AI writing assistant designed as an all-in-one tool that lets you craft fresh SEO-friendly content faster. With LongShot, you can save 2-4 hours in research and writing, thanks to features like Blog Wizard, Headline Generation, and Meta Description and Summary Generator. There are over 40 dedicated features in LongShot AI that make it suitable for a wide range of use cases. . Its notable features include a FAQs generator, headline generator, content rephraser, and content claim detection. Additionally, it has several tools for copywriting, such as the AIDA Copywriting Framework Generator and the PAS Copywriting Framework Generator. Key features Enables real-time collaboration
Reads and writes in eight languages, including French and Spanish
Custom AI template
Lets you fact check your content
Access to 15 unique niches for personalized content Pricing Pricing varies depending on the number of users. The prices shown below are quoted for three users, billed monthly: 2 weeks free trial
Premium – $6(billed annually)
$6(billed annually) Pay As You Go – $19/ One Time 6. JECT.AI Finding fresh news angles can be challenging for journalists. JECT.AI uses artificial intelligence to help editors, freelance journalists, and PR and marketing agencies, identify emerging trends, receive potential news stories, discover content for research, and access new resources to develop news. JECT.AI manipulates information sourced from millions of published news articles and publications to give you recommendations for news angles and voices. It can analyze the sentiment of published information, giving users more complex angles for writing. Furthermore, it can help journalists specializing in scientific writing, giving them access to science audience personas and communication metaphors. Key features Supports six languages, including English, German, and Norwegian
Can be integrated with your archives
Simple plug-ins for text editors like Google Docs and WordPress Pricing Get in touch with JECT.AI representatives for pricing 7. Descript Descript is an all-in-one tool that you can use for audio and video journalism. With it, you can edit recordings by script, remove filler words like “um” and “you know,” do overdubs, and access templates for quicker video editing. Journalists can use Descript to create explainer videos, social media posts, and podcasts. It also enables collaboration, anytime, anywhere, thanks to its ability to sync to the cloud. Furthermore, it lets users share their videos online while keeping their branding and incorporating an interactive transcript. Key features Easy to use
Studio Sound capability for studio-quality recordings
Access to premium stock media
Lets you export 4k videos faster Pricing Descript offers a free plan, as well as three other pricing plans: Hobbyist – $12 per month, billed annually
$12 per month, billed annually Creator – $24 per month, when billed annually
$24 per month, when billed annually Business – $40 per month, when billed annually 8. Vetted Vetted has developed an Expert Discovery Platform enabling journalists to contact verified news sources directly. It has been used by journalists at Forbes, USA Today, The Washington Post, and Bloomberg, among other global news organizations. To use Vetted as a journalist, search for the experts you need for your story. You can filter results using filters such as the source’s years of experience and area of expertise. Once done, you can directly send secure messages to your selected source. Lastly, Vetted lets you save a list of your favorite sources. Experts on Vetted undergo the platform’s vetting process, requiring them to have multiple years of relevant experience, a verified LinkedIn profile, and no known history of providing false or misleading information. Key features Easy to use
Connects journalists with vetted sources Pricing $79 one-time Verification Fee 9. Narrativa The Narrative is a natural language generation platform that uses machine learning to automate content and news. Using Narrativa, journalists can access features like automatic content generation for long-tail content and headlines and the Narrativa Knowledge Graph, which helps you create customized and relevant content for your audience. The Wall Street Journal uses it to generate use via Narrativa’s AI system, Gabriele. Using the generated text, users can add their own analysis or additional information to fine-tune the text. Narrativa can also be used in other industries, such as financial services, marketing, entertainment, and life sciences. Key features Automated content generation
Its tech stack includes natural language processing, natural language generation, and data analysis Pricing Life Sciences – starting from $2,999/month
starting from $2,999/month Financial Services – starting from $5
starting from $5 Marketing & Ecommerce – starting from $5
starting from $5 Media & Entertainment – starting from $5 10. Article Forge Article Forge uses advanced artificial intelligence and machine learning to help writers generate SEO-optimized long-form content faster and easier. With Article Forge, you can create different articles for various industries, including local news, marketing, entertainment, and health. It uses intelligent algorithms to research different topics and write richer content. To start using Article Forge, enter relevant details, such as your keyword and article length. Wait until the AI content generator researches and generates your article. Once done, you’ll be able to receive the finished piece. Key features User-friendly
Articles generated using Article Forge have passed Copyscape and have no duplicate content
Offers a five-day free trial and a 30-day money-back guarantee
Supports seven languages Pricing Pricing varies according to the number of words per month and the number of users. The estimate shown below is for 25,000 words per month and one user: $27 per month when billed monthly
$13 per month when billed annually
Contact Article Forge for Business pricing
Related Content: 7 Content Optimization Tools You Need to Try Today
What Is Content Writing? (+ How to Excel At It In 2024)
13 Best Copywriting Practices – Writing for the Web in 2024
Why Use AI Tools in the Newsroom?
AI tools enable journalists, editors, and reporters to be more productive and efficient. These facilitate writing and content creation, leveraging the capabilities of artificial intelligence, machine learning, deep learning, and natural language processing to help journalists research and write stories. These can also aid you in looking for reliable sources and finding facts. Plus, some of these tools also enable real-time collaboration, which helps boost productivity and efficiency.
Given that they speed up the research and writing process, AI tools allow you to scale when and how you deliver the news. It’s worth noting that while some of these AI tools are capable of automatically generating content, these still need to be checked, analyzed, and verified by journalists, editors, and publishers. However, there’s no denying that these AI tools can save you a lot of time and resources regarding researching and writing.
In addition to the points above, different news organizations have different needs, so it’s crucial to determine whether or not a particular tool can meet your requirements. The good news is that many of the AI tools available for journalists are relatively easy to use. So, even if you’re not a developer, you’ll still be able to use them.
Pros & Cons of AI in Journalism
AI tools have revolutionized the journalism industry, offering numerous benefits but also presenting some challenges. Here, we explore the key pros and cons of integrating AI into journalism, with examples from leading tools such as Jasper.ai, Pinpoint, and QuillBot.
Pros of AI in Journalism
Increased Efficiency and Speed
AI tools like Jasper.ai significantly enhance productivity by automating content generation. Jasper.ai can create SEO-optimized articles, social media posts, and advertising copy up to ten times faster than traditional methods. This acceleration allows journalists to focus more on investigative work and in-depth reporting.
Enhanced Content Quality
Tools like QuillBot offer advanced paraphrasing and grammar checking, ensuring that articles are not only accurate but also engaging and well-written. The Content Improver feature in Jasper.ai also helps refine drafts, making them more compelling and reader-friendly.
Advanced Data Analysis
Pinpoint, part of Google’s Journalist Studio, leverages AI to analyze large volumes of documents and extract key insights. This capability is invaluable for investigative journalism, where understanding and synthesizing vast amounts of data can uncover significant trends and stories that would otherwise remain hidden.
Cons of AI in Journalism
Risk of Homogenization
One potential downside of AI-generated content is the risk of homogenization. While tools like Jasper.ai are trained to match the user’s writing style, there is a possibility that reliance on AI could lead to a less distinctive voice in journalism.
Ethical and Accuracy Concerns
Although AI tools like Pinpoint and QuillBot offer robust fact-checking and analysis features, there is still a risk of inaccuracies. Journalists must remain vigilant and verify the information provided by AI to avoid the dissemination of false or misleading content.
Dependence on Technology
As journalists increasingly rely on AI tools, there is a risk of over-dependence on technology. This could potentially reduce the development of critical thinking and investigative skills among journalists, as they might lean too heavily on AI for research and writing tasks.
By weighing these pros and cons, media professionals can make informed decisions about integrating AI into their workflows, ensuring they harness its benefits while mitigating potential drawbacks.
How to Choose the Best AI Tools for Journalists?
Selecting the right AI tools can be a game-changer for journalists, enhancing productivity and the quality of their reporting. Here’s a guide to help you choose the best AI tools tailored to your needs, ensuring you stay ahead in the fast-paced world of journalism.
Assess Your Specific Needs
Before diving into the plethora of AI tools available, identify the specific needs of your newsroom or personal workflow. Are you looking for tools that can generate content quickly, like Jasper.ai, or do you need something that helps with data analysis and fact-checking, such as Pinpoint? Understanding your primary requirements will narrow down your options and ensure you invest in the right tools.
Evaluate Ease of Use
User-friendliness is crucial when adopting new technology. Tools like QuillBot offer intuitive interfaces that simplify tasks such as paraphrasing and grammar checking. Similarly, Jasper.ai’s straightforward setup and integration with other platforms can save you time and reduce the learning curve. Opt for tools that are easy to use and can seamlessly integrate into your existing workflow.
Check for Customization and Flexibility
AI tools that offer customization can significantly enhance your productivity. For instance, Jasper.ai’s pattern recognition feature tailors content to match your writing style, while QuillBot allows you to adjust the level of vocabulary change and paraphrasing modes. Look for tools that provide flexible options to suit your unique needs and preferences.
Consider Pricing and Value
Budget constraints are always a factor, so it’s important to consider the pricing and value of each tool. Tools like Jasper.ai offer various pricing plans based on usage, while others like Pinpoint are free to use with full access available upon request. Compare the cost against the features and benefits to ensure you get the best value for your investment.
Explore User Reviews and Case Studies
Research user reviews and case studies to get a real-world perspective on the effectiveness of the tools. Understanding how major organizations like The Boston Globe and HarperCollins use these AI tools can provide insights into their practical applications and benefits. Reviews from fellow journalists can also highlight potential challenges and advantages you might not have considered.
Case Study: Jasper.ai
HarperCollins uses Jasper.ai to streamline the creation of SEO-optimized articles, social media content, and email campaigns. The tool’s Creative Story and Content Improver features help authors craft compelling narratives, while the Pattern Recognition feature ensures content consistency. This has allowed HarperCollins to increase its content output significantly while maintaining high-quality standards.
Case Study: Pinpoint by Google
The Boston Globe leveraged Pinpoint’s capabilities to quickly sift through thousands of pages of documents, uncovering critical information that shaped their reporting. This ability to handle large data sets efficiently underscores Pinpoint’s value in investigative journalism.
Wrapping Up
While these AI tools are already competent and powerful, there’s no replacing the skill and experience of journalists and writers. One way you can look at these tools is that they can augment your capabilities by bringing advanced technology to the table. Thus, you’re able to create stories and content faster.
Furthermore, there are many ways to use such AI tools' capabilities. Aside from automating content generation, they can collect data and turn them into easy-to-understand visuals, enhance video and audio content, get new ideas for headlines, repurpose old content, and find fresh news angles.
Frequently Asked Questions What are the best AI tools for journalists? Some of the best AI tools for journalists that we’ve found include Jasper, Connexun, LongShot, Pinpoint, and JECT.AI. Can AI tools improve the accuracy and reliability of news reporting? Yes, AI tools can significantly enhance the accuracy and reliability of news reporting. Tools like VerifactAI assist in verifying facts and detecting misinformation, while automated transcription services ensure precise documentation of interviews and statements. This helps journalists maintain high standards of accuracy and credibility in their reporting. What are the ethical considerations when using AI in journalism? The use of AI in journalism brings up several ethical considerations, such as the potential for bias in AI-generated content, the need for transparency about AI's role in content creation, and the risk of over-reliance on AI tools which might undermine the journalistic integrity. It’s crucial for journalists to use AI responsibly and maintain human oversight in the editorial process. How can journalists integrate AI tools into their workflow without compromising their unique voice and style? Journalists can integrate AI tools by using them as assistants rather than replacements. For instance, AI can help with preliminary drafts, research, and transcription, allowing journalists to focus on refining the narrative, adding their unique voice, and ensuring the content aligns with their editorial standards. The key is to use AI to enhance human creativity and judgment, not to replace it.
| 2023-02-06T00:00:00 |
2023/02/06
|
https://influencermarketinghub.com/ai-tools-for-journalists/
|
[
{
"date": "2023/02/06",
"position": 7,
"query": "AI journalism"
}
] |
How Might ChatGPT Impact Journalism and Media ...
|
How Might ChatGPT Impact Journalism and Media Education?
|
https://comminfo.rutgers.edu
|
[] |
A new analysis by Professor of Journalism and Media Studies John V. Pavlik reveals both positive and negative attributes of the new generative AI Chatbot ...
|
“What is the meaning of journalism and its function?” Professor of Journalism and Media Studies John V. Pavlik asked ChatGPT. The Chatbot answered him immediately. Its response, Pavlik said, “was three paragraphs that were well written, and made sense, and I basically agreed with it. I thought, even I would have a hard time writing three more coherent paragraphs.”
Intrigued, Pavlik decided to next ask ChatGPT a series of questions designed to elicit much more of its knowledge of the history of journalism. Pavlik wanted to see the types of answers a student might receive from ChatGBT. “Right now, a big fear among educators is that students will plagiarize ChatGPT,” Pavlik said, “so I wanted to pull some research together to help reveal both the positive and the negative aspects of this new Chatbot.”
His analysis, “Collaborating With ChatGPT: Considering the Implications of Generative Artificial Intelligence for Journalism and Media Education,” was published in Journalism and Mass Communication Educator on January 7, 2023.
ChatGPT, which was first launched by Open AI on November 30, 2022, (its development is being partly funded by Microsoft), is a generative AI natural language tool that answers in “complete sentences that seem authoritative and are presented as common knowledge” without referencing its sources, Pavlik said. Revealing its sources may be something it soon does, especially since a competing tool, Perplexity.ai already does so.
As he anticipated, Pavlik’s research identified ways that ChatGPT could possibly enhance journalism and media education, as well as a longer list of ways it might pose problems and even dangers.
A positive, Pavlik found, is ChatGPT could potentially be useful as a reference or search tool to provide background information or ideas, in much the same way students and journalists already use Google search for that purpose.
Comparing ChatGPT to other tools we use to enhance education and research such as Microsoft Excel, Pavlik said, “We use spreadsheets to help us with numbers, so we don’t have to do the math ourselves all the time, and there is nothing wrong with letting the computer do the adding and subtracting.”
Pavlik’s list of potential concerns is much longer, however. At the top of the list are issues concerning plagiarism, ethics, bias, and intellectual integrity.
The possibility of students using ChatGPT to plagiarize is a serious problem, Pavlik said. “The danger is that students, rather than write content themselves, will let ChatGPT write it and then change a few words around so they think they did not literally plagiarize from ChatGPT. That’s where I see the real potential damage.”
Ensuring the intellectual integrity of information sourced from ChatGBT is also critical, Pavlik said. “Whether the lack of integrity is in the form of plagiarism, or the creation of things that are synthetic but are presented as real, it will be essential for the user to ensure the integrity of their work isn’t somehow compromised by ChatGPT.
“ChatGPT users need to thoroughly research any factual assertion and information that ChatGPT makes or provides, double-checking it all for accuracy, completeness, and bias, because there is no way to know without conducting additional fact-checking research whether its response is correct, or mostly right, or really far off.”
Beyond the classroom, Pavlik said he anticipates that unscrupulous actors, whether they are affiliated with governments, political figures, or corporations, will use generative AI tools such as ChatGPT to create content to manipulate public understanding and the views of the public.
These mis-and dis-information campaigns could be subtle but also rampant, he said, because ChatGPT is so fast. An enterprise that perhaps at one time would have required dozens of workers to create fake content, Pavlik said, could now just use one computer and ChatGPT.
He was inspired to ask ChatGPT the initial question, and then undertake the study, Pavlik said, when he was conducting research on potential bias in the images DALL-E, another generative AI Chatbot, produces. “The news media are already using DALL-E to create content,” Pavlik said. “For example, Cosmopolitan created its June 2022 cover using DALL-E.”
Pavlik noted there are significant differences between ChatGPT and DALL-E. “Every DALL-E image has a watermark embedded in it that indicates it came from DALL-E. Also, one of the stipulations of using DALL-E is users must indicate that they created the image with DALL-E. But with ChatGPT, at least currently, there isn’t a mechanism that builds a marker into the text that can’t be removed. Open AI might be working on that, but even a marker wouldn’t solve the plagiarism, bias, and ethics problems because students could just retype ChatGPT’s content.”
He plans, he said, to share his analysis in his SC&I journalism and media studies courses, including Digital Media Ethics, Digital Media Lab, and Digital Media Innovation.
Addressing ChatBot’s inability (or refusal) to provide sources for its information and opinions, Pavlik said, “In terms of just quoting ChatGPT as a source, my perception right now is that generative AI is going to continue to evolve, but at the moment, most people might be embarrassed to say they relied on ChatGPT. It’s like saying your source is your Amazon Echo.”
Discover more about the Journalism and Media Studies major and department on the Rutgers School of Communication and Information website.
Image: Created by SC&I Professor John V. Pavlik using DALL-E. The text prompt he used to generate the image was: "Surrealistic painting of a Rutgers professor contemplating the impact of artificial intelligence on journalism."
| 2023-02-06T00:00:00 |
https://comminfo.rutgers.edu/news/how-might-chatgpt-impact-journalism-and-media-education
|
[
{
"date": "2023/02/06",
"position": 13,
"query": "AI journalism"
}
] |
|
Research Tools for Media & Journalists
|
Research Tools for Media & Journalists
|
https://www.lexisnexis.com
|
[] |
... AI · Lexis+ · CounselLink+ · Lexis Analytics · Practical Guidance · Nexis+ AI · Nexis · Nexis Data+ ... Nexis® for Media and Journalism. Identify credible ...
|
*Due to the nature and origin of public record information, the public records and commercially available data sources used in reports may contain errors. The LexisNexis Public Records services are not provided by “consumer reporting agencies,” as that term is defined in the Fair Credit Reporting Act (15 U.S.C. §, et seq.) (“FCRA”) and do not constitute “consumer reports,” as that term is defined in the FCRA. Accordingly, these LexisNexis services may not be used in whole or in part as a factor in determining eligibility for credit, insurance, employment or another eligibility purpose in connection with which a consumer report may be used under the FCRA.
| 2023-02-06T00:00:00 |
https://www.lexisnexis.com/en-us/professional/research/media.page
|
[
{
"date": "2023/02/06",
"position": 59,
"query": "AI journalism"
}
] |
|
University of Michigan improves AI text summaries ...
|
University of Michigan improves AI text summaries of academic journals
|
https://www.oracle.com
|
[] |
Using Oracle Cloud Infrastructure AI, University of Michigan creates summary system for long documents used in research, journalism, and legislation.
|
For this project, the researchers used high-performance virtual machines and remote NVIDIA A100 Tensor Core graphical processing units (GPUs), which proved effective for running the team’s memory-hungry summarization algorithms. The university used BM.GPU4.8, which contains 8 GPU cards at 40 GB of memory each. These high-performance GPUs sped up the training of the researchers’ models and the validation of their hypotheses.
The university used this computational power to build a new NLP system by improving the efficiency of existing language-generation models and increasing the document length accepted by those models. The ability to consume more words allowed the summarization system to analyze long documents in their entirety, instead of processing a truncated version. An NLP model that can read the full document also improves the accuracy of the facts in the generated summaries, as the system becomes aware of all the information available.
This new software generated summaries that more accurately captured the core content of long documents, supporting new research, journalistic articles, government reports, and more. In their experiments, Michigan researchers found that longer document lengths led to more accurate summaries, as measured by both human assessment and automatic metrics.
| 2023-02-06T00:00:00 |
https://www.oracle.com/customers/university-of-michigan/
|
[
{
"date": "2023/02/06",
"position": 82,
"query": "AI journalism"
}
] |
|
How AI streamlines high volume hiring
|
How AI streamlines high volume hiring
|
https://tengai.io
|
[] |
AI for recruiting can automate the screening process and help you quickly identify candidates that possess the skills, knowledge and experience that your ...
|
As a human resource professional, you know that high-volume recruitment can be a big headache. It takes a lot of time and often overlooks qualified candidates. The solution is to use artificial intelligence (AI) for recruiting. AI can help you sift through job applications quickly and efficiently, so you can find the best candidates for the job. In addition, AI can help you identify qualified candidates who might otherwise be overlooked. So if you're looking to open up the bottleneck of job applications, AI is the answer.
What is AI for recruiting?
AI for recruiting represents the integration of automation into the high-volume recruitment process. Machine learning tools screen qualified job candidates, as well as automate processes such as conducting initial interviews.
Automated technology streamlines the high-volume recruitment process, especially when it comes to completing repetitive procedures. AI recruiting software accesses the massive amounts of data you store in your Applicant Tracking System (ATS). Advanced AI for recruiting allows recruiters to perform blind screenings, with a dramatic reduction in personal bias.
Learn how Tengai makes it easy to identify the right talent in a high-volume hiring process, while also creating an exciting experience for every applicant.
What are the benefits of AI for high volume hiring?
Recruiters benefit from high-volume recruitment technology in two primary ways.
1. You save time
As a recruiter, you know that there's always more than enough to do and not enough hours in the day. You're continually trying to work smarter, not harder. Well, there's good news - AI can help!
By taking on some tasks that are currently eating up your time, AI frees you up to focus on other important recruitment tasks. For example, rather than reviewing every resume that comes in, AI can screen them for you. This not only saves you time, but it also saves your company money.
2. You hire the best job candidates
If you're in the process of recruiting for a new position at your company, you may be wondering if AI can help improve the quality of the candidates on your shortlist. The answer is a resounding yes!
AI for recruiting can automate the screening process and help you quickly identify candidates that possess the skills, knowledge and experience that your company is looking for. This not only saves you time and energy, but it also leads to happier employees that are less likely to leave your company because of dissatisfaction with their role. In addition, automating your recruiting process can also help to lower turnover costs by reducing the need to constantly train new employees. So if you're looking for ways to improve the quality of your job candidates, AI is definitely worth considering.
What recruiting tasks you can automate with AI technology
How do you use AI technology for high-volume hiring? The possibilities are seemingly endless. Let’s look at some of the most common tasks you can automate below.
Job candidate outreach
The first item on your to-do list should be to develop the technological infrastructure that opens high-volume recruitment channels. AI for recruiting automates the process for matching job candidates with specific open positions. By automating the process of searching through resumes and applications, and conducting initial screening interviews, you can free up your team's time to focus on more important tasks.
Not only will this improve your team's efficiency, but it will also ensure that you're able to identify the best candidates for the job. In addition, using AI for recruiting can help to create a more diverse pool of candidates, as it removes any unconscious bias that may exist in your team's hiring decisions.
Reviewing applications
If you're in charge of high-volume recruitment, you know that sifting through hundreds of applications is the most time-consuming part of the process. But what if there was a way to speed things up? Enter AI recruiting assistants.
These advanced tools can analyze more application information faster than the human eye, making it easier to identify qualified candidates. In addition, AI recruiting assistants can learn and adapt over time, meaning they'll get better and better at finding the right candidates for your needs. So if you're looking for a way to streamline your high-volume recruitment process, an AI recruiting assistant may be just what you need.
Screening candidates
In today's job market, it's more important than ever to ensure that you are hiring the best possible candidates for every open position. With so many qualified applicants to choose from, it can be difficult to know where to start. That's where AI recruiting software comes in. By filtering out candidates that don't meet your specific criteria, an AI-powered Applicant Tracking System (ATS) can help you save time and money in the recruitment process. In addition, using AI for recruiting allows you to spend more time with the top candidates, getting to know them on a personal level and learning about their qualifications. As a result, you can be confident that you are making the best possible hiring decisions for your company.
Scheduling interviews
If your team of recruiters needs to spend more time with the most qualified candidates, then AI can help out by handling the scheduling of interviews. Advanced AI recruiting software can schedule, reschedule and send out reminders about interview dates and times, freeing up your team so they can focus on other things. Plus, the AI can keep track of which candidates have been interviewed and how they did, so you can make more informed hiring decisions.
Innovations for high-volume recruitment
Automation continues to evolve for the development of high-volume recruitment strategies. However, the main goal of eliminating inefficiencies remains the focal point for human resources professionals.
Intelligent Screening Software
AI recruiting software includes a program that automates the resume screening process. The intelligent software learns which employees that your company hired went on to have long, successful careers. Evaluating the success of an employee considers factors such as tenure and performance.
As this type of AI recruiting software compiles data., machine learning automatically modifies the way your company screens employees.
Conversational AI
Chatbots have made their way into the future of work.
Recruiter chatbots, which undergo constant modifications, provide real-time interaction for job candidates. The chatbots are programmed to ask questions in a certain order based on the answers a job candidate provides.
Recruiter chatbots also answer questions from job candidates, as well as provide information on the next steps in the recruitment process.
Digital interviews
One of the most amazing components of AI recruiting software is the ability to assess every candidate’s choice of words and patterns of speech. The AI recruiting software also recognizes a large number of non-verbal cues, such as facial expressions and nervous hand movements.
The technology is most effective as a validation tool for recruiters that have developed their own assessments of job candidates.
How AI will change the role of a recruiter
The future of AI for recruiting might be augmented intelligence.
Augmented intelligence is the concept that states you cannot replace the skills of humans with technology. As HR consultant Michael Haberman said, “Augmented Intelligence, rather than totally replacing people at work, will be used to make them more effective. I think this may be the best use of AI for HR.”
Using augmented intelligence will change the role of recruiters in three ways. First, recruiters can be more proactive during the hiring process. Second, recruiters will have more time to spend building personal relationships with job candidates. Finally, recruiters will have the ability to close the loop with hiring managers much faster than they do now.
In Summary
Before AI, high-volume recruitment represented a long, drawn-out process that alienated some job candidates. Using AI for recruiting saves you time while improving the accuracy of your candidate assessments. The major challenge for integrating automation into your recruitment process involves analyzing more data. However, the data will produce a better pool of job candidates who want to stay with your company for years to come.
Staying on top of the rapid changes concerning AI technology should be your HR team’s focus over the next 10 years. The reward for your team’s diligence will be a much more efficient high-volume recruitment process.
Automate your high-volume recruitment process with Tengai
Our digital hiring tools are perfect for high-volume recruiting, reduce the time-to-hire, help to find the best candidate, and fill the position quickly.
With Tengai, it is possible to include all candidates in the screening phase and still save time. Tengai's interview is interactive; each applicant always receives instant feedback after completing the screening. Unlike a static video interview where you record yourself answering questions, conversational AI engages candidates in real time. The interactive meeting is unique because it feels just like a real conversation – only smarter, more effective, and more engaging.
Learn how Tengai will help you improve the way you screen, assess and hire talent. Book a demo with our team today.
| 2023-02-06T00:00:00 |
https://tengai.io/blog/ai-for-high-volume-recruitment
|
[
{
"date": "2023/02/06",
"position": 9,
"query": "artificial intelligence hiring"
}
] |
|
AI Brilliantly Enhances Recruitment Capacity
|
AI Brilliantly Enhances Recruitment Capacity
|
https://weareeverise.com
|
[
"Justine Everise"
] |
Everise automates candidate screening with AI-driven bots, mimicking human interactions for efficient and aligned decision-making in recruitment.
|
For talent acquisition professionals, finding the right applicant is hard work. Add superpowers to your recruitment team with our AI-powered candidate screening software. Download this case study to learn how Everise does it.
With the use of artificial intelligence, Everise automates the candidate screening process through bots that are developed to resemble human interactions and make decisions that are closely aligned with your own.
| 2023-01-19T00:00:00 |
2023/01/19
|
https://weareeverise.com/artificial-intelligence-brilliantly-expands-your-recruitment-and-hiring-capacity/
|
[
{
"date": "2023/02/06",
"position": 25,
"query": "artificial intelligence hiring"
}
] |
Talently.ai: Your AI Interviewer
|
Talently.ai: Your AI Interviewer
|
https://interview.talently.ai
|
[] |
Our AI interviewing tool enhances the internship hiring process, allowing you to efficiently assess and select the most promising young talent who will bring ...
|
Campus Hiring
Experience a Smarter & Faster Approach to Campus Hiring
Talently.ai filters out the top talent across universities through multiple assessments without biases. It streamlines hiring and keeps students engaged throughout the process with no geographical restrictions. This gives you diverse candidates with the right skills faster, all with a smooth, flexible experience.
Learn more
| 2023-02-06T00:00:00 |
https://interview.talently.ai/
|
[
{
"date": "2023/02/06",
"position": 30,
"query": "artificial intelligence hiring"
}
] |
|
ChatGPT Will Lead to Layoffs, But Traders Say They ...
|
ChatGPT Will Lead to Layoffs, But Traders Say They Will Be Fine
|
https://www.bloomberg.com
|
[
"Nate Lanxon"
] |
Advanced artificial intelligence systems are expected to eventually replace some jobs in the financial, media, legal and technology sectors.
|
Advanced artificial intelligence systems are expected to eventually replace some jobs in the financial, media, legal and technology sectors, according to the latest MLIV Pulse survey.
What's more striking: More than two-thirds of 292 respondents, predominantly in the financial sector, didn't view their own jobs as being at risk any time soon.
| 2023-02-06T00:00:00 |
2023/02/06
|
https://www.bloomberg.com/news/articles/2023-02-06/chatgpt-adds-to-reasons-for-layoffs-in-big-tech-journalism-finance
|
[
{
"date": "2023/02/06",
"position": 9,
"query": "artificial intelligence layoffs"
}
] |
NSA Bills Itself as a 'Soft Landing Place' for Laid off Tech ...
|
NSA Bills Itself as a 'Soft Landing Place' for Laid off Tech Workers
|
https://www.nextgov.com
|
[
"Edward Graham"
] |
The intelligence agency has been quietly moving over the past few months to recruit talented workers affected by the wave of layoffs at tech companies and ...
|
As the tech sector continues to experience a massive wave of layoffs—with tens of thousands of workers let go over the past several months by behemoths like Alphabet, Amazon, Meta and Microsoft—the National Security Agency is joining the ranks of other federal agencies positioning themselves to benefit from the industry’s contraction.
Molly Moore, NSA’s deputy director of workforce support activities, told Nextgov that “we absolutely are trying to take advantage of these tech layoffs” to bolster the agency’s tech and cyber workforce. She said these efforts have included “augmenting [our] current recruitment strategy to reach these audiences through social media, participation at job fairs and expanding the locations of job postings.”
In a tweet last month responding to another users’ tweet about openings in the tech sector amid the wave of layoffs, NSA cybersecurity director Rob Joyce noted that NSA was hiring for cybersecurity, capability development and signals intelligence—or SIGINT—positions, and offered “an amazing stable opportunity if that is now a priority.”
Moore said that, when it comes to enticing talented tech workers to apply to the NSA through social media engagement, “tweets, like Rob’s, don’t hurt.”
“We are at an inflection point, where cybersecurity is a national imperative,” Joyce told Nextgov in a statement. “NSA is looking to bring in top-talent from early to mid-career/life stages across a variety of skill sets. Whether you’re new to NSA or the [intelligence community], or you’ve worked here before, there’s a path for you at NSA to be a part of this cutting-edge, fast-paced mission.”
In addition to more targeted candidate recruitment and social media outreach, NSA is leveraging existing internal services to streamline the hiring process for applicants coming from the private sector, as the agency seeks to expand its operations. This has included using a communications dashboard to enhance engagement with NSA applicants. The dashboard, which first went live in at the end of June 2022, has seen its use increase in recent months as the agency works to keep interested applicants informed about the agency’s hiring procedures and activities through more direct outreach.
In a January press release, NSA announced that it was “undertaking one of its largest hiring surges in 30 years with openings for over 3,000 new employees.” Moore said that over half of the positions NSA is hiring for are in cyber- and tech-related roles, including openings for “software engineers, systems engineers, capabilities development specialists, cybersecurity professionals, analysts, mathematicians and data scientists.”
To better recruit these talented workers, Moore added that the agency’s intent is “to dedicate resources to try to streamline some of the processes” around hiring—efforts that included an initial, more targeted recruitment drive which has evolved into a broader hiring campaign.
From October through December, NSA ran a LinkedIn recruitment initiative that contacted identified tech workers “who were affected by that first wave of layoffs” rippling through the tech sector, according to Moore.
Christine Parker, senior strategist for talent management at NSA, told Nextgov that this initial campaign—which she said resulted in “an influx of applications”—entailed “reaching out via LinkedIn to people who had those tech companies in their profiles,” as well as “putting some social media information out there, getting on job boards like CareerBuilder and Indeed and putting some notes on our intelligencecareers.gov site, where you can go and look up NSA’s open vacancies.”
NSA launched a second tech-focused hiring campaign on Jan. 9 to expand the scope of its initial recruitment drive, with an emphasis once more on using LinkedIn to contact laid off tech workers and leveraging social media to spread the word about the agency’s vacancies. This new effort—which the agency plans to run through mid-March—is designed, in part, to “keep up with the companies that are experiencing layoffs,” and to “put messages out there that NSA is a soft landing place for people,” according to Parker.
An NSA spokesperson told Nextgov that, to date, the agency’s recruitment efforts have resulted in the agency hiring approximately 1,000 new employees for tech, cyber, intelligence and business positions.
“We do have more specific activities that we're going to try to undertake, including really trying to apply additional resources to the hiring of these folks, and really trying to shepherd people through the process,” Moore added, citing the difficulties that workers from the private sector can face when trying to navigate the government’s hiring platforms.
Parker said the agency’s communications dashboard has helped to overcome some of these challenges by providing applicants with more direct information about the hiring process, such as updates on their applications and answers to any questions that they might have.
“A single recruiter isn't going to be able to send a personal message to every applicant in their portfolio,” Parker said. “The dashboard lets us do that at a larger volume with some targeted messaging—it might not be 100% personal, but it’s targeted. And it’s helping people know we're still here, that we’re tracking you and we know you're in our pipeline and we still want you to come on board at the end of this process.”
NSA is also factoring longer-term national security priorities into its recruitment efforts. Moore cited comments that Gen. Paul Nakasone—NSA director and the commander of U.S. Cyber Command—and Defense Department officials previously made about China being America’s “pacing challenge” to underscore some of the intelligence issues that NSA is looking to address with its new hires.
“How do we posture ourselves to be ready to really take on that challenge?” Moore asked. “That will require language analysts, it will require intelligence analysts. So it really covers the whole scope of job roles and fields that we have here.”
Other federal agencies are also working to pivot their hiring and recruiting efforts to take advantage of the tech sector’s wide-reaching layoffs. The Department of Veterans Affairs launched a hiring initiative in late 2022 to help fill roughly 1,000 tech-related vacancies across the department. VA’s chief people officer told Nextgov last month that the recruitment drive has helped the department fill more than 25% of its tech-focused vacancies, with hundreds of candidates waiting in the pre-selection stage.
When it comes to enticing laid off tech workers to join NSA, Moore said that potential applicants should consider the invaluable contributions that their skills could have on NSA’s intelligence and security operations moving forward.
“NSA is here, we're hiring stable and we work on really hard problems,” Moore said. “And so we really are looking for some of the best and brightest to help us with those problems.”
| 2023-02-06T00:00:00 |
2023/02/06
|
https://www.nextgov.com/digital-government/2023/02/nsa-bills-itself-soft-landing-place-laid-tech-workers/382636/
|
[
{
"date": "2023/02/06",
"position": 20,
"query": "artificial intelligence layoffs"
}
] |
Big Tech's Mass Layoffs: Implications For The Economy & ...
|
Big Tech’s Mass Layoffs: Implications For The Economy & Employers
|
https://www.wellable.co
|
[] |
The formerly booming tech industry is experiencing a significant turndown, marked by mass layoffs at major firms like Amazon, Alphabet, Meta, and Microsoft.
|
The formerly booming tech industry is experiencing a significant turndown, marked by mass layoffs at major firms like Amazon, Alphabet, Meta, and Microsoft. The most recent company to join them was IBM, which announced they would be laying off 3,900 employees. While Silicon Valley has faced contractions in the past, this current turndown is unprecedented for the tech industry, known for its resilience in the face of economic challenges due to its size and widespread presence.
In 2022, the tech sector dismissed almost 200,000 employees, a 694% increase compared to the previous year. In January of this year alone, an additional 40,000 employees were dismissed. Four of the biggest US tech companies accounted for 51,000 of the total tech layoffs announced in the last few months:
Alphabet: In January of this year, Alphabet, the parent company of Google, announced its plan to cut 12,000 jobs or 6% of its workforce.
In January of this year, Alphabet, the parent company of Google, announced its plan to cut 12,000 jobs or 6% of its workforce. Microsoft: By March 2023, Microsoft will have cut 10,000 jobs or about 5% of its workforce.
By March 2023, Microsoft will have cut 10,000 jobs or about 5% of its workforce. Meta: In November of 2022, Facebook-owner Meta Platforms reported cutting over 11,000 jobs or 13% of its workforce.
In November of 2022, Facebook-owner Meta Platforms reported cutting over 11,000 jobs or 13% of its workforce. Amazon: In January of this year, Amazon announced that it would cut 18,000 jobs or 6% of its workforce.
Source: Reuters • THE HINDU GRAPHICS
When considering hiring freezes, the cuts do not fully capture the sudden halt in the industry’s fortunes.
Real Reasons Behind Layoffs
Global tech giants have attributed these mass layoffs to a need to reduce expenses as economic growth slows. However, the financial burden doesn’t appear to be the real reason for the cuts.
Microsoft announced its plans to invest $10B in OpenAI, the creators of viral platform ChatGPT, and Alphabet claimed that its capital will be redirected to their “highest priorities”; both statements were made simultaneously with the layoff announcements. So, what are the real reasons behind the cuts?
Reversing Pandemic Hiring: Record-breaking demand and profits led tech firms to engage in large-scale recruitment efforts during the pandemic, offering aggressive salaries and benefits to snag top talent. The layoffs could reflect a move to reverse this trend, especially considering the significant number of long-term employees who were let go, indicating a desire to cut high-wage staff.
Record-breaking demand and profits led tech firms to engage in large-scale recruitment efforts during the pandemic, offering aggressive salaries and benefits to snag top talent. The layoffs could reflect a move to reverse this trend, especially considering the significant number of long-term employees who were let go, indicating a desire to cut high-wage staff. Replacing Human Workers With Artificial Intelligence: Human resources positions took the harshest hit, accounting for 28% of all layoffs. While this could be partially due to the reduced need for recruitment, HR functions are quickly being replaced by automation. Amazon, amongst other firms, reported using AI to identify low-performing employees and fire them. It’s likely that firms are advancing towards replacing some jobs with machines given the developments and cost-effectiveness of AI technology.
Economic Impact
Big spenders drive recession-recovery, and the US economy depends heavily on the spending of the top 20%. Tech workers, who are typically well compensated, are within the elite of spenders—those who can drop money on expensive dinners, homes, event seating, and vacations without a second thought. They are critical to service sectors and businesses that rely on voluntary spending.
Tech layoffs are surging and those lucky enough to keep their jobs can expect smaller bonuses and fewer advancement opportunities. Meanwhile, other sources of income are plateauing. While there may not be a complete drop-off in consumer spending, a gradual decline in discretionary spending is expected as people become increasingly cautious.
Big Tech Layoff Takeaways
The Cuts Are Monumental: Meta, Amazon, Microsoft, and Google together have terminated over 51,000 jobs in the past few weeks, a record-breaking number for the historically resilient industry and an abrupt turnaround from the pandemic hiring surge. Big Tech Is Not Struggling: While there have been minor profit decreases for Big Tech companies within the past year, the Silicon Valley Giants are still among the most profitable and valuable corporations worldwide. Most Laid-Off Tech Employees Are Back On Their Feet: A survey revealed that eight out of 10 laid-off techies find a new gig within three months of their job search, with 40% of them finding one within a month. Executives Cite A Need To Reduce Spending: Executives of Big Tech corporations attribute the layoffs to preparing for the uncertain economic landscape ahead, one fraught with high inflation, recession fears, and limited consumer spending. Artificial Intelligence Is A Considerable Factor: While economic instability probably plays some part in the layoffs, it could also reflect the transition towards replacing workers with artificial intelligence to cut costs and maximize efficiency. Tech Is A Major Economic Driver: The tech industry significantly impacts the US economy, employing nearly 9 million people and adding $1.8 trillion to the economy. The performance of Big Tech companies greatly affects local economies, people’s investments, and other industries, which often make decisions based on the stability and growth of the tech industry. Consumer Spending Is Expected To Decrease: As layoffs continue to impact tens of thousands of people, particularly those in the tech industry, consumers will be more frugal in their spending.
How to Support Remaining Employees After Layoff
Laying off employees can be a difficult decision for any employer, and it can have a significant impact on the remaining staff. To maintain morale and productivity, it’s important for employers to provide support to their remaining staff during this transition. Check out the ways employers can create a positive and understanding work environment after a layoff.
| 2023-02-06T00:00:00 |
2023/02/06
|
https://www.wellable.co/blog/big-techs-mass-layoffs-implications-for-economy-and-employers/
|
[
{
"date": "2023/02/06",
"position": 21,
"query": "artificial intelligence layoffs"
}
] |
The Rise of the Robot Reporter - Metalika
|
The Rise of the Robot Reporter
|
https://metalikamachines.com
|
[] |
As reporters and editors find themselves the victims of layoffs ... But for companies that figure out how to work with it, artificial intelligence could be a boon ...
|
As reporters and editors find themselves the victims of layoffs at digital publishers and traditional newspaper chains alike, journalism generated by machine is on the rise.
Roughly a third of the content published by Bloomberg News uses some form of automated technology. The system used by the company, Cyborg, is able to assist reporters in churning out thousands of articles on company earnings reports each quarter.
The program can dissect a financial report the moment it appears and spit out an immediate news story that includes the most pertinent facts and figures. And unlike business reporters, who find working on that kind of thing a snooze, it does so without complaint.
Untiring and accurate, Cyborg helps Bloomberg in its race against Reuters, its main rival in the field of quick-twitch business financial journalism, as well as giving it a fighting chance against a more recent player in the information race, hedge funds, which use artificial intelligence to serve their clients fresh facts.
The Age of Artificial Intelligence
| 2023-02-06T00:00:00 |
https://metalikamachines.com/news/news-1/
|
[
{
"date": "2023/02/06",
"position": 73,
"query": "artificial intelligence layoffs"
}
] |
|
There Are Big Tech Layoffs Nowadays. Here Is a List of Stable ...
|
There Are Big Tech Layoffs Nowadays. Here Is a List of Stable Industries For Programmers
|
https://codegym.cc
|
[] |
According to tech job tracker layoffs.fyi, there have been more than 200,000 tech jobs lost since the start of 2022. Actually, the tech industry is confronting ...
|
Massive Layoffs in Numbers
Tesla
Robinhood
Snap
Shopify
Stripe
What Are the Reasons?
The Best Industries for Software Developers
Retail
Research and Development
Government and Defense
Healthcare
Education
Top Reason to Choose Java
Conclusion
During the past decade, the tech sector experienced explosive growth and huge demand for specialists. And things got even hotter when the Covid-19 pandemic ravaged the world and moved more businesses online. Tech hiring blazed across Silicon Valley more rapidly, and tech giants like Amazon and Facebook even doubled the number of workers to stay apace with the increasing demand… No longer. The last year has become game-changing for most industries, including the IT field.According to tech job tracker layoffs.fyi , there have been more than 200,000 tech jobs lost since the start of 2022. Actually, the tech industry is confronting one of its worst contractions in history, with Google, Microsoft, Amazon, and Meta announcing additional mass layoffs over the span of a few upcoming months. What’s happening, and is there a future for tech land?So far, Google, Microsoft, Amazon, and other big companies have already laid off more than 70,000 employees and striving for more. Google has recently announced that the company plans to lay off 12,000 people , while Microsoft said it’s letting go of 10,000 employees. Amazon also began a new round of job cuts within the company that will eliminate about 18,000 employees and become the largest workforce reduction in its history. Meta, in its turn, announced its most significant round of layoffs in November 2022. The company said it planned to eliminate 13% of its staff (more than 11,000 employees). Shortly after closing the $44 billion purchase of Twitter in October 2022, Elon Musk cut around 3,700 workers, which equals nearly half the staff. Besides the aforementioned companies, there were also critical rounds of lay-offs in the following well-known companies:(6,000 jobs cut),(1,100 jobs cut),(1,000 jobs cut),(1,000 jobs cut),(1,100 jobs cut).Why are so many IT companies laying people off? Does it all come down to the need to reduce costs as global economic growth is increasingly slowing down right now? Let’s be real, the aforementioned companies aren’t teetering on the edge of bankruptcy. Instead, they experienced record-breaking profits not so long ago. And, of course, this money couldn’t evaporate so quickly. The thing is, investors have changed their minds about how they’re evaluating companies. In fact, when companies are growing fast, and their revenue is reaching 20-30% a year, nobody cares about profits. But when the revenue is slowing down, investors become more cautious. In other words, as the revenue of the companies accelerated greatly through the pandemic in 2020-2021, they hired too many people. Then happened the economic downturn in 2022. Hence, the reductions. Without a doubt, the majority of big companies have tens of billions of dollars in reserves, and they think it’s relevant to invest in something new rather than support all operations. For example, Microsoft, which announced the reduction of around 10,000 employees, simultaneously stated that it’s going to invest $10 billion in OpenAI. Similarly, Google’s parent company called Alphabet has also said it’s reducing its workforce by 12,000 people whilst planning to invest in its own “AI-powered answer to ChatGPT.” Of course, it’s not the only reason for the massive cutbacks… It shouldn’t come as a surprise that global economics lives its worst times, and many companies really experience a financial crisis. What is shocking, however, is that the average level of experience of those tech specialists who were fired makes approximately 11.5 years. The possible reason for this is that more experienced workers earn higher wages, and by reducing them, businesses can meet their financial goals and survive. So, it’s not all those junior developers with little experience that are at risk. What is positive, laid-off techies have pretty good job prospects. Recent research by ZipRecruiter shows that laid-off specialists have landed back on their feet pretty quickly. Actually, 8 out of 10 techies who lost their job found a new one after three months of being axed (almost 40% of them found a new tech job within one month of starting their search). As icing on the cake, in the US alone, the wage growth reached historic highs, especially for workers switching jobs (50% higher in November 2022 than it was for people staying in their jobs).From this, it’s easy to conclude that tech skills are always in “high demand” across the economy.” And what is notable, the demand for tech workers goes beyond big tech firms and traditional startups. Coders, engineers, cybersecurity professionals, data experts, mobile app developers, and AI engineers can find a place in many other industries.A few decades ago, software engineers had nothing in common with a career in retail. But today, the retail industry employs nearly the same number of software engineers (if not more) than Silicon Valley. Modern retailers are doing their best to create something unique and outperform their competitors. To stand out in this digital age, some companies are even blowing up their entire infrastructures and building new microservices platforms. So, the retail industry is always in need of UI/UX professionals, mobile developers, and DevOps specialists. Do note that in most cases, retailers are looking for specific skills – they want to hire developers who understand not only the relevant technologies but customers' needs as well. Therefore, be ready to go beyond writing code. You should also understand consumer products and what clients want if you’d like to tie your career to retail.This sphere is vast. It involves a host of game-changing product labs, research and development groups, as well as specific business units requiring specific types of software engineers. Speaking about the brightest examples, we can consider the $12.6-billion media company called “Thompson Reuters,” which is going to re-invent video news for the next generation. The company plans to offer personalized TV news delivered via mobile phones and needs many developers to turn this project to life.Nowadays, almost all serious spheres and businesses have become digital, and the government-industrial complex stands at the forefront of that “digitalization.” That’s why it desperately needs software programmers, big data analysts, and professionals with strong cyber-security skills. The most significant tech trends in government include public service automation, cloud computing, AI & data analytics, cybersecurity, digital citizen identity, and government data management.Medical care is something people will always need and will always spend money on, no matter what’s going on in the economy. People still willingly spend money on their health and health-related services. Currently, there are about 350,000 mobile health apps spread throughout different app marketplaces, and the worth of the mHealth market was estimated at $63.88 billion in 2022. And it’s expected to grow at an incredible CAGR of 18.2% up to $243.57 billion by 2030.Simply put, mobile health becomes the go-to solution for healthcare providers, patients, and stakeholders. Numerous applications continue to revolutionize the ways of accessing healthcare services – scheduling appointments, contacting doctors via chats or calls, providing reminders for taking medication, searching for health information, etc. Besides that, we can also see the rise of cloud-based technologies in the healthcare industry, utilization of big data, and integration of AI. The healthcare application development world is really exciting, and its future looks bright.The same goes for the educational sector, which can do nothing without technology today. Online learning gives students an opportunity to acquire knowledge faster, easier, and cheaper than ever before. Not to mention, eLearning can be a real salvation during the pandemic. Education extensively relies on mobile learning, AI chatbots, and gamification methods in e-learning apps. No doubt, the impact of EdTech on the education industry is huge. Consequently, the demand for skilled specialists is huge too.As you have seen, software development plays a central role in many industries. So, we bet there will be an increase in demand for software developers in the long run. Following on from all the said above, it’s also easy to conclude that Java will stay one of the core programming languages in both start-ups and big multinational companies. Why? Because Java boasts a base everywhere, making it an optimal choice for AI, ML, big data, IoT, blockchain, and other emerging trends across all industries. Without a doubt, a Java-related career is also going to be very rewarding.No denying that global economics is experiencing tough times. But, as you see, there are numerous industries that extensively rely on technology and are in high demand for IT professionals. If you’re a skilled Java developer, there is definitely a place under the sun awaiting you. All that being said, be ready to showcase not just your technical know-how. Great communication skills, problem-solving, and teamwork are essential qualities for a top developer. CodeGym can help you with hard skills, whereas your self-control, motivation, and passion can help you with soft skills. So, let’s work in tandem!
| 2023-02-06T00:00:00 |
https://codegym.cc/groups/posts/1029-there-are-big-tech-layoffs-nowadays-here-is-a-list-of-stable-industries-for-programmers
|
[
{
"date": "2023/02/06",
"position": 84,
"query": "artificial intelligence layoffs"
}
] |
|
The ripple effects of layoffs
|
The ripple effects of layoffs
|
https://www.bbc.com
|
[] |
In tech, for instance, companies cut more than 150,000 workers in 2022, according to tracking site Layoffs.fyi; this year already, they've trimmed almost 76,000 ...
|
Academics and other experts are adamant that for many who are laid off – as well as for many of those who remain after their companies makes sweeping cuts – these effects will linger. Worse still, the more frequently layoffs are executed as an ostensibly necessary step to counteract economic headwinds, the more engrained they will become in the culture of business and the more normalised they will be. This leaves workers in a deeply precarious position, as they steep in the fear of losing their job at any moment.
| 2023-02-03T00:00:00 |
2023/02/03
|
https://www.bbc.com/worklife/article/20230203-stress-anxiety-global-layoffs
|
[
{
"date": "2023/02/06",
"position": 86,
"query": "artificial intelligence layoffs"
}
] |
Is C3.ai Artificial Intelligence Product Suite a Gamechanger?
|
Is C3.ai Artificial Intelligence Product Suite a Gamechanger?
|
https://www.entrepreneur.com
|
[
"Jea Yu"
] |
... ai and keep those clients that may otherwise have to cancel their contracts amid normalization and layoffs. It also makes onboarding new clients more ...
|
Every day has ushered in more and more headlines covering the AI platform ChatGPT as it becomes more and more mainstream. Artificial intelligence (AI)
This story originally appeared on MarketBeat
Every day has ushered in more and more headlines covering the AI platform ChatGPT as it becomes more and more mainstream. Artificial intelligence (AI) platforms have been around for over a decade, like International Business Machines Corp. (NYSE: IBM) AI platform Watson which launched in 2011.
However, it's finally becoming useful in everyday applications for everyday people, and the general public is eating it up. The key has been the parent company OpenAI's GPT-3 series language model, which has evolved for over a decade. It will improve with more usage, and it's getting plenty of that.
From writing term papers to computer programs and cooking recipes, ChatGPT has captured the attention and imaginations of over 100 million users worldwide in January 2023, only launching two months prior. Its investors include Tesla Inc. (NASDAQ: TSLA) CEO Elon Musk and Microsoft Inc. (NASDAQ: MSFT), who initially invested $1 billion in OpenAI and will be investing up to $10 billion as it incorporates ChatGPT into its applications.
ChatGPT has kicked off the AI trend in stocks for 2023. One of the most notable and easy-to-remember stocks leading the rally has the appropriate stock symbol AI. Enterprise AI platform provider C3.ai Inc. (NASDAQ: AI) stock has shot up 35% since our MarketBeat Originals article covering the stock less than two weeks ago.
Enterprise AI
ChatGPT is tailored for mainstream applications and has announced a $20 per month ChatGPT Plus subscription option. C3.ai has been providing enterprise AI for over a decade. C3.ai provides companies with a scalable AI platform as a turnkey solution to predictive modeling. It is a crucial benefactor of the growth of AI. Its platform can accommodate non-coding to deep coding for developers. It was named a 2022 Forrester Wave Leader in the AI and Machine Learning Platforms.
C3.ai Generative Suite Launch in March 2023
The C3 Generative AI Product Suite assimilates the latest AI capabilities from Open AI, academia, and Alphabet Inc. (NASDAQ: GOOGL). ChatGPT and GPT-3 are incorporated into C3 AI's enterprise products.
On Jan. 31, 2023, C3.ai announced the launch of its first product in its C3 Generative AI Product Suite called C3 Generative AI for Enterprise Search. It allows enterprise users to use its natural language interface to quickly locate, acquire and present all relevant data across a company's information systems.
The C3 Generative AI Product Suite entrenches advanced transformer models with its pre-built AI applications. It speeds up the client's ability to leverage the models. C3 Generative AI will speed up business and industry transformations in the supply chain, aerospace, utilities, oil & gas, sustainability, financial services, healthcare, defense, and intelligence.
C3.ai president Thomas Siebel commented, "C3 Generative AI fundamentally changes the human-computer interaction model of enterprise application software. Combining the full potential of natural language, generative pre-trained transformers, enterprise AI, and predictive analytics will change everything about enterprise computing."
A Gamechanger
The former commanding general of the U.S. Army Cyber Command, retired Lt. General Ed Cardon, commented, "This is game-changing for U.S. DoD, game-changing for the U.S. intelligence community, and game-changing for ubiquitous information access and insight. This technology breakthrough can help dissolve the biggest barrier to effective action, which is access to timely, accurate information and insight at all levels of the organization."
Consumption-Based Pricing Model
C3 earnings suffered in the short term as it switched over to a consumption-based model. It caused C3.ai to guide down its fiscal Q3 2023 guidance as new clients will only be paying small upfront costs. The consumption model enables more flexibility for companies during economic contractions, which helps lower churn for C3.ai and keep those clients that may otherwise have to cancel their contracts amid normalization and layoffs. It also makes onboarding new clients more economical.
It should pay off in the long run, just like when companies switched to cloud-based software-as-a-service (SaaS) subscription models.
Descending Triangle to Rounding Bottom to Cup and Handle
Our previous article detailed the breakout of the weekly descending triangle formation on the rise through $12.65, further accelerating the weekly market structure low (MSL) trigger through $13.02. The continued extension forms a rounding bottom on the weekly chart as it approaches the cup lip at $23.58, where the descending triangle also commenced in August 2022.
The weekly 20-period exponential moving average (EMA) sits at $14.63, and 50-period MA sits at $16.68, both support levels now. The weekly stochastic continues to rise towards the 80-band. A pullback from the lip line will form the handle, either continuing to sell off or bounce and breakout through the lip line to trigger the cup and handle breakout.
Pullback supports sit at $16.59, $15.51, $14.04, $13.02, and $12.65.
| 2023-02-06T00:00:00 |
2023/02/06
|
https://www.entrepreneur.com/finance/is-c3ai-artificial-intelligence-product-suite-a/444447
|
[
{
"date": "2023/02/06",
"position": 91,
"query": "artificial intelligence layoffs"
}
] |
Educators need to understand and embrace artificial ...
|
Educators need to understand and embrace artificial intelligence writing tools
|
https://edsource.org
|
[] |
ChatGPT and other artificial intelligence, or AI, writing tools can generate humanlike stories, essays, poems and other written forms.
|
July 10, 2025 - Hundreds of thousands of children could lose federally-funded food stamps and health care under the new law.
Credit: Allison Shelley for American Education
ChatGPT and other artificial intelligence, or AI, writing tools can generate humanlike stories, essays, poems and other written forms. Writers can use these tools in many ways, including as a muse that inspires ideas; a co-author that helps craft text; a reviewer that provides constructive feedback; an editor that checks the details; or a ghostwriter that writes without credit.
Educators have many concerns about the impact of these powerful tools on teaching, learning and using writing in schools. Should some uses of AI be considered appropriate, while others are treated as a modern form of plagiarism? Should students master certain writing skills before being allowed to use AI tools? Can we monitor how students use them? Do AI tools fundamentally change what students need to learn and how they should be taught?
A common initial response is to ban the use of ChatGPT. However, bans will be futile as AI writing capabilities become widely available and integrated into word-processing programs. We must accept that AI tools are changing how writing is accomplished in every field and embrace that students need to learn to use them effectively.
Reforming writing in schools requires careful consideration because it will involve changes in curriculum standards, teaching practices, student assessments, teacher preparation and education policies. In some ways, this parallels past changes in mathematics education, in which calculators went from being banned to being required. These changes take time and cannot move as quickly as AI tools are advancing.
Limitations of AI writing tools
The impressive capabilities of AI writing tools come with important limitations for educators to consider, including the following:
AI systems do not replicate human knowledge, cognition or emotion. AI systems are trained by processing an enormous corpus of digital text. By contrast, much of human knowledge stems from goal-driven activities, social interactions, modeling of others and other interactions in the real world. These experiences lead to embodied understandings of causes and effects; emotional intelligence involving understanding others’ needs, motives and perspectives; a sense of family, community and culture; and, perhaps most importantly, a sense of self. AI will never match the richness of the human experience.
AI writing quality is limited. Since AI-generated text is based on patterns found in the training texts, it often has a dull, written-by-committee style that lacks engaging and creative writing. In addition, AI tools are limited in handling complex ideas, so their output is often overly simplistic and fails to be convincing.
AI systems are often outdated. AI systems are trained when created and are not continuously updated, so they can produce outdated information and fail to respond well to requests that require timely knowledge.
AI systems can produce harmful content. The internet materials used to train AI systems can include racist, sexist, homophobic and other forms of offensive content. As a result, AI can generate unintended (or intended) toxic outputs.
AI systems can lack veracity. AI tools can fabricate statistics, historical events, quotes, references and all sorts of other information, often producing authoritative-sounding text that is simply untrue.
Writing with AI tools
Given the limitations, AI tools do not produce quality text at the push of a button. Using them effectively requires that students learn to do the following:
S et directions for the goals, content, audience and style, which often involves writing parts of the text to guide the AI tool about what it is to produce.
et directions for the goals, content, audience and style, which often involves writing parts of the text to guide the AI tool about what it is to produce. P rompt the AI to produce the specific outputs needed, often providing separate prompts for each desired outcome, which can range from individual sentences to a complete report or story.
rompt the AI to produce the specific outputs needed, often providing separate prompts for each desired outcome, which can range from individual sentences to a complete report or story. A ssess the AI output to validate the information for relevance, accuracy, completeness, bias, timeliness and writing quality. Assessment can lead to revising the directions and prompts and having AI generate alternative versions of the text.
ssess the AI output to validate the information for relevance, accuracy, completeness, bias, timeliness and writing quality. Assessment can lead to revising the directions and prompts and having AI generate alternative versions of the text. C urate the AI text to select what to use and organize it coherently, often working from multiple versions generated by AI along with human-written materials.
urate the AI text to select what to use and organize it coherently, often working from multiple versions generated by AI along with human-written materials. Edit the combined human and AI contributions to produce a well-written document.
These steps, which form the acronym SPACE, encompass new forms of human-computer interactions to accomplish writing tasks.
Educators must understand and embrace the changes driven by advances in AI, and it is time to begin the challenging work of reforming how we teach students to write with AI tools. Success will require collaborations of educators, researchers, AI experts, policymakers and others across the public and private sectors, focusing on what students need to learn to be successful in the AI-augmented world in which they will — and already do — live.
•••
Glenn M. Kleiman, Ph.D., is a senior adviser at the Stanford Graduate School of Education’s Accelerator for Learning. He was previously executive director of the Friday Institute for Educational Innovation and professor of education at North Carolina State University.
The opinions in this commentary are those of the author. If you would like to submit a commentary, please review our guidelines and contact us.
| 2023-02-06T00:00:00 |
https://edsource.org/2023/educators-need-to-understand-and-embrace-artificial-intelligence-writing-tools/685299
|
[
{
"date": "2023/02/06",
"position": 3,
"query": "artificial intelligence education"
}
] |
|
What is generative AI? An AI explains
|
What is generative AI? An AI explains
|
https://www.weforum.org
|
[
"This Article Is Published In Collaboration With",
"Visual Capitalist"
] |
Generative AI refers to a category of artificial intelligence (AI) algorithms that generate new outputs based on the data they have been trained on.
|
Generative AI refers to a category of AI algorithms that generate new outputs based on the data they have been trained on.
It uses a type of deep learning called generative adversarial networks and has a wide range of applications, including creating images, text and audio.
While there are concerns about the impact of AI on the job market, there are also potential benefits such as freeing up time for humans to focus on more creative and value-adding work.
Generative AI Explained by AI
After years of research, it appears that artificial intelligence (AI) is reaching a sort of tipping point, capturing the imaginations of everyone from students saving time on their essay writing to leaders at the world’s largest tech companies. Excitement is building around the possibilities that AI tools unlock, but what exactly these tools are capable of and how they work is still not widely understood.
We could write about this in detail, but given how advanced tools like ChatGPT have become, it only seems right to see what generative AI has to say about itself.
Everything in the infographic above – from illustrations and icons to the text descriptions—was created using generative AI tools such as Midjourney. Everything that follows in this article was generated using ChatGPT based on specific prompts.
Without further ado, generative AI as explained by generative AI.
Generative AI technologies have exploded into mainstream consciousness Image: Visual Capitalist
Generative AI: An Introduction
Generative AI refers to a category of artificial intelligence (AI) algorithms that generate new outputs based on the data they have been trained on. Unlike traditional AI systems that are designed to recognize patterns and make predictions, generative AI creates new content in the form of images, text, audio, and more.
Generative AI uses a type of deep learning called generative adversarial networks (GANs) to create new content. A GAN consists of two neural networks: a generator that creates new data and a discriminator that evaluates the data. The generator and discriminator work together, with the generator improving its outputs based on the feedback it receives from the discriminator until it generates content that is indistinguishable from real data.
Generative AI has a wide range of applications, including:
Images: Generative AI can create new images based on existing ones, such as creating a new portrait based on a person’s face or a new landscape based on existing scenery
Text: Generative AI can be used to write news articles, poetry, and even scripts. It can also be used to translate text from one language to another
Audio: Generative AI can generate new music tracks, sound effects, and even voice acting
Generative AI can generate content through neural network Image: Visual Capitalist
Disrupting Industries
People have concerns that generative AI and automation will lead to job displacement and unemployment, as machines become capable of performing tasks that were previously done by humans. They worry that the increasing use of AI will lead to a shrinking job market, particularly in industries such as manufacturing, customer service, and data entry.
Generative AI has the potential to disrupt several industries, including:
Advertising: Generative AI can create new advertisements based on existing ones, making it easier for companies to reach new audiences
Art and Design: Generative AI can help artists and designers create new works by generating new ideas and concepts
Entertainment:Generative AI can create new video games, movies, and TV shows, making it easier for content creators to reach new audiences
Overall, while there are valid concerns about the impact of AI on the job market, there are also many potential benefits that could positively impact workers and the economy.
In the short term, generative AI tools can have positive impacts on the job market as well. For example, AI can automate repetitive and time-consuming tasks, and help humans make faster and more informed decisions by processing and analyzing large amounts of data. AI tools can free up time for humans to focus on more creative and value-adding work.
ChatGPT is a type of text generation AI Image: Visual Capitalist
How This Article Was Created
This article was created using a language model AI trained by OpenAI. The AI was trained on a large dataset of text and was able to generate a new article based on the prompt given. In simple terms, the AI was fed information about what to write about and then generated the article based on that information.
In conclusion, generative AI is a powerful tool that has the potential to revolutionize several industries. With its ability to create new content based on existing data, generative AI has the potential to change the way we create and consume content in the future.
| 2023-02-06T00:00:00 |
https://www.weforum.org/stories/2023/02/generative-ai-explain-algorithms-work/
|
[
{
"date": "2023/02/06",
"position": 73,
"query": "artificial intelligence graphic design"
}
] |
|
Are You Going to Lose Your Job? 10 Warning Signs
|
Are You Going to Lose Your Job? 10 Warning Signs
|
https://staffingnetwork.com
|
[
"Sean Vayser"
] |
Restructuring could lead to combined positions, altered job titles, and job loss ... Largely due to artificial intelligence (AI), the job search process has ...
|
When changes are happening at work, it is common for employees to worry about their jobs. For example, sometimes poor earnings and budget cuts lead to layoffs. And even when a company is fiscally healthy and growing, there can be cutbacks when there are departmental changes and priority shifts.
If you are worried you will lose your job, consider speaking with professionals who can advise you on who is hiring should you find yourself looking for work. Doing so can help you to feel in control of your career, whether your workplace downsizes or not. And talking to a career expert at Staffing Network today could introduce you to new opportunities for the future.
10 Indicators You May Lose Your Job
Reduction of hours. If your full-time job is suddenly part time, it is a sign your position may be less important to the organization than it was in the past. Leadership wants to change processes. Restructuring could lead to combined positions, altered job titles, and job loss. Other positions are being cut. If you have heard of individuals being furloughed from teams or know of employees being laid off, more job cuts could follow. An acquisition or merger is being discussed. When one company is acquired by another, jobs may be eliminated. For instance, if each company has a purchasing department, the possibility that there are redundant positions is high. You are no longer getting along with your manager. Conflict could be an indicator of your position being on shaky ground. Email and meeting invites have stopped. If you were involved in many meetings and message threads but now find yourself excluded, it could be an indicator of team plans that do not include your position. You have been receiving poor performance reviews. Negative reviews are something to take note of, if you have received a poor review at work, calmly talk to your supervisor about how you could improve your performance. Documentation has increased. When there is a lot of human resource documentation, and the notices and write ups aren’t positive, this gathering of paperwork could be part of the process of letting you go. Fewer projects are being assigned to you. If you don’t have much work to do, or significantly less than you used to have, reducing your position to elimination could occur. You’ve been told layoffs are coming. Whether you were informed casually over a friendly lunch with your boss or the information was shared at a formal meeting, if you are told there will be layoffs, don’t ignore the news.
Strategically build your professional network when experiencing job loss concerns. Then, you will know there are positions waiting for you in case you are let go. A great way to begin these relationships is to reach out to a well-established staffing firm, such as Staffing Network.
Are you scared of being furloughed, laid off, or fired? Focus on what you can control, talk with professionals who can help. Staffing Network is a full-service staffing and recruiting firm that specializes in light/skilled industrial, engineering, and operations professionals. Connect with Staffing Network today.
| 2023-02-07T00:00:00 |
2023/02/07
|
https://staffingnetwork.com/are-you-going-to-lose-your-job-10-warning-signs/
|
[
{
"date": "2023/02/07",
"position": 46,
"query": "AI job losses"
}
] |
Loss of jobs due to transformation
|
Loss of jobs due to transformation
|
https://www.vda.de
|
[] |
The electrification of new car fleets will lead to significant employment losses in the automotive industry, and also in other sectors.
|
The automotive industry is unreservedly committed to the goal of climate neutrality by 2050. Various technologies are available to achieve this goal. To achieve the interim CO 2 target in 2030 (-37.5% compared with 2020), battery-electric powertrains take priority within this amount of time. At the same time, hydrogen and e-fuels will be established as further means of propulsion.
However, the switch to battery-electric powertrains will result in significant employment losses. This is the conclusion of all studies that have been published on this subject in recent years. One such study by the BMWI from 2019 ("Automotive value creation 2030/2050"; Roland Berger et al) puts the loss of employment at 170,000 employees in the automotive industry alone (manufacturers and suppliers) in the event of 80% of passenger cars manufactured being electric. This would correspond to a loss of more than 18% compared to the number employed in the automotive industry in 2017. This is true even taking into account that the electrification of the powertrain also creates new jobs, e.g., for the assembly of electrical components and their integration in the vehicle.
In addition to the employment losses in the automotive industry, there are also losses in those sectors upstream and downstream of the industry. For example, jobs are lost in the sectors "metal products, rubber and plastic products or foundry products." Jobs are also lost in the aftermarket, e.g., in auto repair shops, because electric powertrains consist of fewer components than conventional ones and are therefore more low maintenance. Overall, the BMWI study assumes further losses of 300,000 employees in the upstream and downstream sectors.
There are two reasons for the employment losses resulting from the electrification of the powertrain: First, far fewer parts are involved in an electric motor and correspondingly fewer parts need to be integrated with each other than in a piston engine (pistons, valves, gears, injection systems, sealing rings, etc.). Secondly, in the case of the battery electric drive, a significant part of the added value is generated outside the EU, namely in Asia. At least this is the case with battery cells, which are still being produced entirely abroad. However, German automakers are in the process of establishing their own domestic battery cell manufacture.
| 2023-02-07T00:00:00 |
https://www.vda.de/en/topics/automotive-industry/loss-of-jobs-due-to-transformation
|
[
{
"date": "2023/02/07",
"position": 89,
"query": "AI job losses"
}
] |
|
Applicant Tracking System Software Market: Future Trends ...
|
Applicant Tracking System Software Market: Future Trends & Forecasts
|
https://gohire.io
|
[
"Chris Smith",
"Sophie Smith"
] |
Employers anticipate that by 2020, 17% of all jobs will be automated. Approximately 94% of US firms are already adopting AI, and robots plan to enhance their ...
|
Applicant tracking system (ATS) is software that simplifies the recruiting process by organising candidates with automated intelligence. This helps the recruiters screen the most and best-qualified candidates based on collected information regarding experience, skillset, and other aspects.
Applicant tracking systems have a vast market, with more than 90% of Fortune 500 companies using the software. It was valued at 2.3 billion US dollars in 2021 and will be approximately 3.2 billion US dollars in the next five years.
With this blog, we bring you the future applicant tracking system trends and forecasts of the applicant tracking system software market - key drivers, challenges, market leaders, and more. So read further to know more!
Market Size and Growth Rate
The introduction of applicant tracking systems (ATSs) to the market in the 1990s marked a turning point in the administration of the hiring process for the businesses that included this solution in their procedures, even though the initial versions were quite basic. Primarily, it made it easier for recruiters to keep track of applications and organise information about each candidate.
Since then, both HR technology and the hiring procedure itself have advanced significantly. Online applications grew in popularity throughout the early 2000s due to extensive internet usage and social media platforms' emergence. Additionally, in recent years, the job market has become more candidate-focused and has included new components like employer branding and candidate experience.
The global applicant tracking system market is growing at a compound annual growth rate (CAGR) of 6.2% from 2020 to 2030.
Market Segments
The platform (or hosting) type and the size of your business are the two main factors that categorise the types of ATS software. The primary ATS categories for the platform type are:
Software as a Service : These vendors of the total, turnkey solutions keep your platform and business data on a cloud-based server. They often offer setup, support, and continuous client success management to make the most of the product. SaaS solutions are becoming increasingly popular because of their simplicity and 24/7 accessibility from anywhere.
: These vendors of the total, turnkey solutions keep your platform and business data on a cloud-based server. They often offer setup, support, and continuous client success management to make the most of the product. SaaS solutions are becoming increasingly popular because of their simplicity and 24/7 accessibility from anywhere. On-site : The business's own IT system keeps these software platforms online. They provide advantages like more flexible security and data maintenance options but demand a lot more maintenance and IT resources.
: The business's own IT system keeps these software platforms online. They provide advantages like more flexible security and data maintenance options but demand a lot more maintenance and IT resources. Integrations: These more compact, modular solutions combine to build an entire ATS platform. ATS integrations are fantastic for smaller businesses with a smaller budget because they let you choose the ones that meet your needs (and no more than you need).
The secondary factor is the size and type of the company - enterprise, SMB, or agency.
Now the question arises - who uses an applicant tracking system?
The majority of large organisations use applicant tracking systems in some capacity. Over 98.8% of Fortune 500 companies, according to a Jobscan study, employ applicant tracking systems (ATS). According to a Kelly OCG poll, 66% of large corporations and 35% of small businesses, respectively. And these figures keep rising.
The truth is that you'll almost certainly encounter an ATS in the following scenarios:
If you're applying to a big company.
If you are using an online application form.
Even job search engines like Indeed and LinkedIn have an internal ATS.
The ATS market is growing in more than just one or two countries. During the projection period, Asia-Pacific is anticipated to grow more rapidly than other regions. Recruiters in the APAC region face a significant problem because of the region's high population density, resulting in numerous job posting applications. As a result of the region's inclusion of nations that place a greater emphasis on these factors, such as Singapore, India, Sri Lanka, Malaysia, and Hong Kong, Asia-Pacific businesses are being informed about the advantages afforded by ATS to overcome this difficulty.
Key Drivers and Challenges
The key driver of the ATS software market is the demand for automation in the recruitment trends. Employers anticipate that by 2020, 17% of all jobs will be automated. Approximately 94% of US firms are already adopting AI, and robots plan to enhance their usage of automation over the next three years. Business executives are aware of the benefits of automating the recruitment process. HR and talent acquisition have been embracing automation and AI technology. Throughout the forecast period, these elements are anticipated to fuel demand for ATS software.
With ease comes challenges, and here are some of them faced while implementing ATS software:
Integration problems: when you are under pressure to reach the "go live" date as soon as possible, ATS software integration problems can be a real pain in the neck. Ensuring that the chosen system is compatible with the ones your business already uses can help to handle this difficulty throughout the ATS selection process. Difficulties during the recruiting process: while an ATS can significantly speed up the hiring process, it cannot perform any magic. Before automating those procedures with the ATS, recruiters must first figure out how to improve the existing system by altering the stages, making the workflow checkpoints clearer, or in some other manner shifting internal focus. Issues while converting: a technical issue could manifest as incapacity or a lack of understanding of transitioning analogue processes to digital ones. So that these can be effectively converted without being completely transformed, the person who defines the rules in the new system needs to have a comprehensive understanding of how the business handles referrals, referral tracking, reference checks, onboarding, and many other important aspects of the hiring trends. Making an ATS mobile-friendly: Even while an ATS may be mobile-friendly, a business may fall short if it doesn't develop a website that employees can use to learn more about the organisation. A company may lose out on mobile traffic that could make up a significant portion of the applicant pool if mobile solutions offered by an ATS are not used.
Future Applicant Tracking System Trends
The scope of ATS software is very high, but it is even higher with the best amalgamation of artificial intelligence and machine learning. Candidate communication may become more fluid with the use of conversational AI interfaces.
Candidates who are hired, their performance on the job, and the information they gave in their application can all be used to train machine learning models. These can screen applications considerably more efficiently than crude keyword-based methods. In addition to candidate screening, applicant tracking software driven by AI offers candidate ranking capabilities that help firms find the most pertinent prospects.
According to John Bersin, only 47% of businesses use HR software that is less than seven years old. These businesses may be encouraged by advancements in machine learning to update or improve their software to boost productivity and shorten the hiring process.
Adopting AI and ML in ATS software can eliminate monotonous tasks, make better decisions, and expose more suitable individuals to job postings. But with the increasing number of smartphone users, the demand for mobile-friendly ATS software is also increasing. Recruiters are also using mobile devices to publish job notifications due to the rise in the use of mobile devices to apply for employment.
Candidates can communicate with recruiters from far-off regions by using mobile devices. For instance, the Monster Jobs mobile app, which is compatible with Android and iOS, was just released by Monster.com. Engagement and feedback, learning and development, employee feedback, performance check-ins, and video interviewing are a few of the apps used in HR procedures.
There are numerous ATS integration types to meet the needs of various recruiters. GoHire provides you with a variety of HR technology integrations:
Job boards integration : to post all the job openings without fuss, we integrate the most useful employment platforms and websites. It is simpler to post the job ad straight through the ATS if the ATS connects appropriately with a variety of job boards. As a result, HR no longer needs to post job adverts on various employment sites and portals individually. You can now significantly reduce the time spent on manual effort.
: to post all the job openings without fuss, we integrate the most useful employment platforms and websites. It is simpler to post the job ad straight through the ATS if the ATS connects appropriately with a variety of job boards. As a result, HR no longer needs to post job adverts on various employment sites and portals individually. You can now significantly reduce the time spent on manual effort. Social media integration : by integrating social media platforms with your applicant tracking system, you may post job openings across various social media networks at once. The data can also be used to determine which platform performs better and draws in a larger talent pool. Thus, you can concentrate your efforts there.
: by integrating social media platforms with your applicant tracking system, you may post job openings across various social media networks at once. The data can also be used to determine which platform performs better and draws in a larger talent pool. Thus, you can concentrate your efforts there. HR software integration : the new hires are automatically added to the payroll and begin receiving training when the ATS is integrated with HR software. As a result, new hires have a seamless onboarding experience and are likelier to promote your business to their friends and family.
: the new hires are automatically added to the payroll and begin receiving training when the ATS is integrated with HR software. As a result, new hires have a seamless onboarding experience and are likelier to promote your business to their friends and family. App integration : if you wish to send mass emails, you may easily integrate your ATS with email marketing software. Without these technologies, sending hundreds of emails to find candidates for open positions is challenging. Sending resumes and other pertinent information to other team members as quickly as possible is made possible by combining the ATS with communication tools like Slack.
: if you wish to send mass emails, you may easily integrate your ATS with email marketing software. Without these technologies, sending hundreds of emails to find candidates for open positions is challenging. Sending resumes and other pertinent information to other team members as quickly as possible is made possible by combining the ATS with communication tools like Slack. Company website integration: the process for the HR team is made simpler by integrating your ATS with your website. Additionally, it makes it simpler for potential employees to learn more about the open roles. Candidates are more likely to apply for the available position in your firm when they can get all the necessary information in one spot without having to search the internet.
Key Players in the ATS Software Market
To improve their market positioning, the key drivers of ATS solutions have adopted various organic and inorganic growth methods, including new product launches, product upgrades, partnerships and agreements, business expansions, mergers, and acquisitions. Some famous players are SAP, ADP, Ultimate Software, Cornerstone, PeopleFluent, iCIMS, IBM, Oracle, and many more.
You will be astonished to find out about the market shares occupied by the key players. We have created a categorised briefing for your convenience:
During the projection period, integration and implementation services are expected to have a sizeable market share.
Large enterprises will hold a larger market share in 2021 based on organisation size.
BFSI will dominate the industry during the forecasted period.
Conclusion
ATSs are crucial for streamlining and automating your hiring process and assisting you in becoming more productive and efficient in your daily responsibilities. They also improve the hiring process, reduce the burden, and boost candidate experience.
However, finding, attracting, and choosing the ideal applicants are not simply the responsibility of ATSs. These are connected to your company branding and recruitment tactics; therefore, it's critical to have a strong strategy before purchasing one.
The market for applicant tracking systems (ATS) is anticipated to grow at an unanticipated CAGR between 2022 and 2029, surpassing 2022 in terms of dollar volume. Investors are still enthusiastic about this industry despite fierce competition because the global recovery applicant tracking system trends are evident, and more fresh investments will continue to enter the sector.
Consider your needs and budget before picking the best applicant tracking systems for small businesses, research the options that best meet those needs, and test drive those options.
Use demo calls with software providers to determine which ATS is ideal for you.
Ask them any questions you have and have them demonstrate their software. After the demo, sign up for a free trial if your preferred vendor offers one, so you can experience the platform yourself.
| 2023-02-07T00:00:00 |
https://gohire.io/blog/applicant-tracking-system-trends
|
[
{
"date": "2023/02/07",
"position": 55,
"query": "AI labor market trends"
}
] |
|
15 Reasons Why You Must Study Artificial Intelligence ...
|
15 Reasons Why You Must Study Artificial Intelligence [+ How to Study] [2025]
|
https://digitaldefynd.com
|
[
"Team Digitaldefynd",
"We Help You Find The Best Courses",
"Certifications",
"Tutorials Online. Hundreds Of Experts Come Together To Handpick These Recommendations Based On Decades Of Collective Experience. So Far We Have Served Million",
"Satisfied Learners"
] |
AI Talent Demand Expected to Surpass 10 Million Roles by 2030. The global AI job market is projected to face over 10 million unfilled roles by 2030 due to a ...
|
Artificial Intelligence is no longer just the domain of tech giants and research labs—it’s a foundational force shaping the way we live, work, and innovate. As AI permeates industries from healthcare to finance, from education to climate science, it’s creating unprecedented opportunities for those equipped to harness its potential. Whether you’re a student aiming to future-proof your career, a professional seeking high-impact upskilling, or an entrepreneur driving innovation, the ability to understand and apply AI is becoming essential.
In this article, we explore 15 powerful reasons why studying AI is one of the most strategic educational moves you can make. Backed by industry statistics and real-world outcomes, these reasons go beyond hype to highlight the actual value AI skills offer in terms of job demand, salary growth, societal relevance, and sustainability. You’ll also find insights on how to approach AI education through structured pathways, projects, and expert-led platforms—including DigitalDefynd, which curates high-quality AI courses for learners around the world. Whether you’re just starting or looking to go deep, this guide will help you recognize why investing in AI learning today leads to long-term success tomorrow.
15 Reasons Why You Must Study Artificial Intelligence [2025]
1. AI Talent Demand Expected to Surpass 10 Million Roles by 2030
The global AI job market is projected to face over 10 million unfilled roles by 2030 due to a persistent talent gap.
Studying Artificial Intelligence gives you access to one of the most in-demand skillsets of the next decade. By 2030, experts estimate that the global economy will need over 10 million skilled AI professionals, but supply is struggling to keep up. Companies across industries—ranging from healthcare and logistics to automotive and banking—are embedding AI at the heart of their operations, generating a surge in new roles such as AI engineers, machine learning specialists, data scientists, and AI policy experts.
Whether you’re just starting out or transitioning from another domain, acquiring AI skills places you at the forefront of job creation trends. Countries like the U.S., Germany, China, and India are launching national AI missions, further boosting demand. A background in AI not only makes you highly employable—it also makes you adaptable to the evolving landscape of intelligent automation, predictive modeling, and data-driven decision-making that will define future work environments.
2. AI Professionals Earn Up to 100% More Than Other Tech Roles as of 2024
In 2024, median AI salaries in top markets like the U.S. and U.K. ranged from $120,000 to $180,000 annually—double that of many traditional tech roles.
Artificial Intelligence has rapidly become one of the most lucrative domains in technology. As of 2024, machine learning engineers and AI specialists in the U.S. earn base salaries that are often 50–100% higher than traditional roles like software developers or IT analysts. Experienced professionals with expertise in areas such as deep learning, computer vision, or generative AI frequently command annual packages exceeding $200,000, especially in high-growth industries like fintech, autonomous systems, and personalized healthcare.
These high salary levels reflect not only scarcity of talent but also the value AI contributes to product development, operational efficiency, and customer engagement. Even non-technical professionals—like product managers, business analysts, or UX designers—who integrate AI knowledge into their work see a notable salary boost. For anyone focused on long-term financial growth, global mobility, and career resilience, investing in AI education is one of the smartest and most rewarding choices in 2024 and beyond.
3. More Than 90% of Businesses Will Use AI in Daily Operations by 2026
By 2026, AI adoption in supply chains, customer service, and business intelligence is expected to exceed 90% across enterprises worldwide.
Artificial Intelligence is no longer a niche experiment—it is now a standard driver of operational excellence. According to forecasts, over 90% of global businesses will integrate AI into at least one core area—such as process automation, customer interaction, or predictive analytics—by 2026. AI-powered chatbots, recommendation engines, fraud detection systems, and robotic process automation tools are already reshaping how organizations deliver services and make decisions.
By studying AI, you not only future-proof your career, but also gain the expertise to contribute directly to strategic business value. You’ll learn how to design intelligent solutions, analyze business-critical data, and collaborate with cross-functional teams on AI initiatives. Whether you’re in tech, finance, retail, or healthcare, understanding how to leverage AI tools and frameworks ensures that you remain relevant, innovative, and indispensable in a digitally transformed future.
Related: Artificial Intelligence Courses
4. AI is Projected to Contribute $15.7 Trillion to the Global Economy by 2030
The global GDP impact of AI is expected to reach $15.7 trillion by 2030, making it one of the biggest economic drivers of the century.
Studying Artificial Intelligence is not just a career move—it’s an entry point into a sector that is fundamentally reshaping the global economy. By 2030, AI is predicted to generate $6.6 trillion in increased productivity and $9.1 trillion through consumption-side effects, transforming how businesses create value. This massive economic uplift will span multiple industries, including retail, manufacturing, healthcare, education, and energy, each adopting AI to unlock new revenue streams and reduce operational costs.
By gaining expertise in AI now, you position yourself at the center of this transformation. You’ll be equipped to help companies tap into intelligent automation, optimize workflows, and create data-driven products and services. Whether you’re aiming to become a founder, innovator, or data strategist, understanding AI will be a core competitive advantage as economies continue to digitize and evolve in an AI-first world.
5. AI Skills Are Among the Top 3 Most In-Demand Competencies for 2024–2030
Global reports rank AI, machine learning, and data science consistently in the top three most desired skills through 2030.
As organizations digitize and prioritize innovation, AI competencies have emerged as critical across nearly all industries. Whether you’re working in tech, law, marketing, healthcare, or education, knowledge of AI—especially in subfields like machine learning, data engineering, and neural networks—is now considered an essential upskilling priority. From 2024 to 2030, surveys of global CEOs and HR executives have consistently listed AI as one of the top three must-have skillsets in the workforce.
Studying AI gives you a multidimensional toolkit: the ability to automate repetitive tasks, extract actionable insights from data, and design intelligent decision-making systems. For employees and entrepreneurs alike, these are skills that future-proof your career and dramatically increase your strategic value in any organization. Whether you’re aiming for leadership roles, transitioning sectors, or staying competitive, AI fluency ensures you’re never left behind.
6. AI-Powered Tools Automate Up to 70% of Routine Business Tasks
AI and automation technologies can eliminate or streamline 60–70% of tasks in sectors like finance, HR, and customer service.
A major reason to study AI is its transformative role in business process automation. In sectors like banking, insurance, retail, and logistics, AI is used to optimize operations, reduce costs, and eliminate human error. Research shows that up to 70% of routine, rules-based tasks—including data entry, report generation, scheduling, and customer queries—can now be handled by AI-powered solutions like robotic process automation (RPA), chatbots, and intelligent document processing tools.
By understanding how to build, deploy, and manage these systems, AI professionals become indispensable to digital transformation efforts. Studying AI equips you with the skills to identify automation opportunities, design efficient systems, and improve decision-making processes across departments. This doesn’t just boost organizational productivity—it also frees up human talent for more strategic, creative, and value-driven roles.
Related: Artificial Intelligence Executive Courses
7. AI Drives Over 30% Higher Efficiency in Healthcare Diagnostics
AI-powered diagnostic tools improve speed and accuracy in disease detection, reducing diagnostic errors by over 30%.
One of the most revolutionary applications of AI is in healthcare, where intelligent systems assist in early disease detection, medical imaging, and treatment planning. AI models trained on massive datasets of X-rays, MRIs, and lab results are now achieving or exceeding human-level performance in diagnosing conditions like cancer, pneumonia, and diabetic retinopathy. In fact, AI can detect certain abnormalities up to 10 times faster than traditional methods, and with significantly lower error rates.
Studying AI allows you to contribute to life-saving innovations that improve patient care and reduce the burden on healthcare professionals. You’ll gain the skills to develop predictive models, build intelligent health assistants, or even optimize hospital resource allocation. As global healthcare systems shift towards data-driven operations, AI knowledge is crucial for anyone interested in public health, medical research, or biotech entrepreneurship.
8. Over 80% of Companies Say AI Is a Key Competitive Advantage
Executives across industries report that AI integration has directly contributed to competitive growth and market leadership.
AI is not just a supporting tool—it has become a strategic differentiator. More than 8 in 10 executives now view AI as essential for sustaining competitive advantage, citing improved customer experiences, faster innovation cycles, and better decision-making as direct outcomes. Businesses that deploy AI are often able to predict customer behavior, personalize services, and optimize supply chains better than their peers.
By studying AI, you position yourself to lead innovation in your organization. You’ll gain the ability to design systems that enhance customer loyalty, reduce costs, and create smarter, scalable solutions. Whether you’re part of a startup or a global corporation, AI education ensures you’re not just reacting to trends—you’re shaping them.
9. AI Skills Increase Freelance Earnings by Up to 60%
Freelancers with AI expertise earn significantly more, often charging premiums 50–60% above average project rates.
For independent professionals and gig workers, AI is a highly bankable skill. Whether you’re offering services in chatbot development, recommendation engines, automated analytics, or predictive modeling, clients are willing to pay a premium for AI-powered solutions. Freelancers who upskill in AI report higher project volumes, better long-term contracts, and stronger client retention.
Studying AI also gives you access to a global freelance marketplace, where demand for specialists continues to rise. Platforms like Upwork and Toptal list hundreds of high-paying projects each month requiring AI model deployment, API integration, or data labeling expertise. With AI in your toolkit, you can diversify your income, choose projects that align with your interests, and build a career that’s flexible, remote-friendly, and high-impact.
Related: Is AI a Good Career Option for Women?
10. AI-Driven Marketing Campaigns Boost Conversion Rates by Over 25%
AI tools improve personalization, timing, and targeting, leading to 20–30% higher conversion rates in digital marketing.
Modern marketing is fueled by data and automation, and AI has become the backbone of high-performing campaigns. AI enables marketers to create hyper-personalized messages, predict customer behavior, and automate everything from email sequencing to real-time ad bidding. These innovations help businesses achieve 25% higher engagement and conversion rates, while significantly reducing customer acquisition costs.
Studying AI allows marketers, content strategists, and brand managers to move beyond intuition into data-driven execution. You’ll learn to use tools like predictive analytics, A/B testing algorithms, and natural language generation to craft impactful campaigns. As customer journeys become increasingly complex, AI-trained professionals are better positioned to deliver value, creativity, and measurable results in competitive digital landscapes.
11. AI Helps Reduce Carbon Emissions Through Smart Optimization
Smart AI systems can cut energy waste by up to 15%, contributing significantly to corporate sustainability goals.
Beyond business performance, AI is also a force for environmental sustainability. AI algorithms are now used to optimize energy grids, forecast renewable energy generation, and reduce industrial emissions. Smart HVAC systems, traffic flow management, and AI-powered waste tracking are helping cities and corporations alike to lower their carbon footprint.
By studying AI, you become part of the global effort to develop green technology and combat climate change. You’ll be equipped to build solutions that enhance energy efficiency, promote resource optimization, and drive sustainable growth. For engineers, researchers, and policymakers passionate about the planet, AI offers a powerful toolkit for designing a cleaner and more resilient future.
Related: AI Interview Questions
12. AI Models Improve Fraud Detection Accuracy by Over 90% in Financial Systems
AI-powered fraud detection systems can identify and prevent suspicious transactions with over 90% accuracy in real-time.
In sectors like banking, insurance, and fintech, AI is redefining how fraud is detected and mitigated. Traditional rule-based systems often miss new or subtle fraud patterns. In contrast, AI models analyze vast datasets in real-time to flag anomalies, inconsistencies, and behavior deviations with exceptional accuracy. This proactive approach helps prevent millions in losses and enhances trust in digital financial services.
Studying AI allows professionals to enter the high-stakes world of fraud analytics, risk management, and cybersecurity. You’ll learn how to build models that adapt to new fraud tactics, use deep learning to recognize patterns, and design explainable AI systems for compliance teams. With the rapid digitization of global finance, AI expertise positions you to safeguard financial ecosystems and play a strategic role in protecting user assets and institutional integrity.
13. AI Literacy Will Be as Important as Digital Literacy by 2030
By 2030, AI literacy is expected to be a fundamental skill for most white-collar jobs, much like digital literacy is today.
As AI tools become embedded in everything from email platforms to decision dashboards, professionals across roles will be expected to understand how these systems work, interact with them effectively, and evaluate their outputs. Just as digital literacy became a prerequisite over the past two decades, AI literacy will soon be non-negotiable, especially for roles in operations, product management, strategy, and analytics.
Studying AI equips you not only with technical skills but with the conceptual understanding needed to collaborate effectively with AI systems, interpret model outcomes, and make informed choices about when and how AI should be deployed. Whether you’re a team leader, educator, or policymaker, AI education ensures you’re not left behind in conversations and decisions that will shape the future.
14. AI-Powered EdTech Can Increase Learning Efficiency by 50%
Adaptive AI tools help learners grasp concepts faster and retain knowledge more effectively, boosting efficiency by up to 50%.
Education is undergoing a quiet revolution powered by AI. Intelligent tutoring systems, adaptive testing, and personalized learning pathways are dramatically improving learning outcomes. Students using AI-driven tools often show faster concept mastery, higher retention, and better performance in both academic and vocational settings. AI’s ability to tailor content to individual learning styles is transforming everything from K–12 classrooms to corporate training programs.
By studying AI, educators and instructional designers gain the skills to design smarter learning platforms, integrate NLP-based chat tutors, and utilize predictive learning analytics. If you’re in the education or L&D sector, AI knowledge enables you to develop tools that empower learners and democratize access to quality education worldwide.
15. AI Will Power 70% of New Product Features by 2035
By 2035, most new software and digital product features will incorporate AI-driven functionality as standard.
From intelligent search to automated design suggestions and predictive UX, AI is becoming a core feature layer in modern digital products. Companies like Google, Microsoft, and Adobe are already embedding AI into productivity tools, creative platforms, and enterprise software, while startups are innovating with AI-first applications in health, finance, logistics, and more. Analysts predict that by 2035, over 70% of new product features will involve AI at their core.
Studying AI prepares you to not only consume these tools but build and shape them. As a product manager, designer, or developer, you’ll be able to prototype AI-enabled features, understand user-AI interaction patterns, and design systems that evolve with use. This gives you a competitive edge in product innovation, customer experience, and future-ready design thinking.
Related: How to Become a Freelance AI Engineer?
How Can You Study Artificial Intelligence?
Artificial Intelligence (AI) is no longer a niche skill—it’s a foundational capability shaping the future of work, business, and innovation. Whether you’re a student aiming to future-proof your career, a working professional seeking to upskill, or an entrepreneur building intelligent products, learning AI opens the door to transformative possibilities. But with the vast landscape of tools, platforms, and specializations, it’s essential to approach your AI education strategically. This section explores the most effective ways to study AI—covering pathways, platforms, project-based learning, and the key skills you need to master to thrive in the age of intelligence.
1. Choose the Right Learning Path Based on Your Background
Your educational and professional experience should guide whether you start with basics or specialize early.
To study Artificial Intelligence effectively, it’s essential to align your learning path with your background. If you’re from a non-technical field, begin with foundational topics like basic Python programming, linear algebra, statistics, and probability. These are critical for understanding how AI models work. Introductory online programs, university courses, and beginner-friendly certifications help bridge this gap, providing the necessary groundwork before diving into core AI topics.
For those with a technical or computer science background, a more direct route into AI subfields such as deep learning, natural language processing (NLP), or computer vision may be appropriate. Structured programs like Stanford’s AI Specialization, MIT’s AI Certification, or curated offerings on DigitalDefynd can help accelerate progress through rigorous content and hands-on projects.
Choosing your path also depends on your career goals—whether you want to become a machine learning engineer, AI researcher, data scientist, or work in AI ethics or product strategy. Your learning journey should be flexible but purpose-driven, combining structured courses with regular reading, experimentation, and participation in AI communities or competitions. By tailoring your entry point and direction, you set yourself up for deeper, more relevant learning as AI continues to evolve.
2. Master Python and Essential AI Libraries Early On
Python powers over 80% of AI systems, and mastering it early accelerates your ability to build real-world models.
Python is the cornerstone of modern AI development due to its simplicity, flexibility, and a vast ecosystem of AI-focused libraries. Whether you’re creating a regression model or a neural network, you’ll use tools like NumPy (numerical computing), Pandas (data manipulation), Matplotlib (visualization), Scikit-learn (machine learning), and deep learning libraries such as TensorFlow and PyTorch. These libraries allow developers to quickly prototype, train, and test models with minimal boilerplate code.
Beginners can start with interactive environments like Jupyter Notebooks, which make it easy to write and test code. Structured learning platforms provide guided tutorials, but consistent practice—such as building small projects, participating in Kaggle competitions, or contributing to GitHub repositories—is key to mastery. Once you’re comfortable with Python, you’ll be able to implement and fine-tune AI models, experiment with algorithms, and debug complex workflows efficiently.
In addition to programming, understanding how these tools integrate into larger AI pipelines—such as for data preprocessing, feature selection, and model evaluation—is crucial. The sooner you become fluent in Python and its ecosystem, the sooner you can transition from theory to practical, deployable AI applications.
3. Build a Strong Foundation in Core Machine Learning Concepts
Over 85% of AI use cases rely on core machine learning techniques like regression, classification, and clustering.
Machine learning (ML) is the engine behind nearly every AI system, making it a critical area of study. A solid ML foundation includes understanding both theoretical principles and hands-on techniques across supervised learning, unsupervised learning, and reinforcement learning. These concepts power applications like recommendation engines, fraud detection, voice assistants, and dynamic pricing systems.
Learning platforms such as edX, Coursera, and DigitalDefynd offer comprehensive programs covering algorithms like linear regression, decision trees, random forests, k-means clustering, and support vector machines. These programs typically include labs and real-world datasets so you can apply what you learn to tangible problems. You’ll also study model evaluation metrics—like precision, recall, F1-score, and AUC—to determine how effectively your models perform.
A key part of ML education is developing intuition about problems like overfitting, underfitting, bias-variance tradeoffs, and cross-validation. These concepts help you build more robust models that generalize well to new data. By mastering ML fundamentals, you’ll unlock your ability to understand advanced AI systems and work across multiple domains—from finance and marketing to autonomous systems and healthcare—where AI plays a growing role.
Related: AI in Supply Chain Management
4. Understand Data Handling and Preprocessing Techniques
Nearly 70% of the time spent on AI projects is dedicated to cleaning, transforming, and preparing data.
Effective AI systems are built on high-quality, well-prepared data. Before any model training begins, one must know how to clean, structure, and preprocess datasets to remove noise, handle missing values, and engineer useful features. Techniques such as normalization, standardization, one-hot encoding, and dimensionality reduction (like PCA) are essential to ensure your data is suitable for machine learning algorithms.
Learning how to work with structured and unstructured data—including images, text, and sensor data—will significantly improve your model’s performance. Tools like Pandas and NumPy make it easier to manipulate datasets, while OpenCV and NLTK help in preprocessing visual and textual data. Understanding data splitting strategies such as train-test-validation splits and cross-validation is also fundamental.
Courses and projects that emphasize real-world datasets from sources like Kaggle or UCI Machine Learning Repository can help you gain confidence in data preparation. Additionally, practicing exploratory data analysis (EDA) will enhance your ability to identify patterns, anomalies, and correlations before modeling. Ultimately, a strong grip on data preprocessing ensures your AI models are accurate, reliable, and production-ready.
5. Learn How Neural Networks and Deep Learning Work
Deep learning algorithms have enabled breakthroughs in computer vision, speech recognition, and language generation.
Deep learning is a subset of machine learning inspired by how the human brain processes information. It uses artificial neural networks (ANNs) to model complex patterns in data. Learning the architecture and functioning of multi-layer perceptrons, convolutional neural networks (CNNs) for images, and recurrent neural networks (RNNs) for sequences is crucial for advanced AI applications.
Frameworks like TensorFlow and PyTorch are widely used to build and train deep learning models. You’ll learn about activation functions, backpropagation, optimizers (like Adam and SGD), loss functions, and epoch tuning. Understanding how to design and fine-tune deep networks helps you tackle sophisticated problems such as image classification, object detection, and natural language translation.
Hands-on projects such as building a digit recognizer using MNIST data or training a sentiment analyzer with movie reviews solidify deep learning knowledge. As AI continues to power technologies like autonomous driving and real-time language translation, deep learning expertise becomes a defining advantage for professionals in both academia and industry.
6. Gain Practical Experience Through Projects and Competitions
Over 60% of AI hiring managers prioritize hands-on project experience over formal degrees.
Learning AI concepts is only half the journey; applying them in real-world scenarios is what truly develops expertise. Working on AI projects, whether independently or as part of a course, builds your problem-solving skills, showcases your ability to handle data, and demonstrates how you think as an AI practitioner. Projects can range from building a movie recommendation system, detecting pneumonia in X-ray images, to predicting stock trends using historical data.
Online competitions—especially on platforms like Kaggle, DrivenData, and Zindi—offer real-time problem statements sourced from companies and researchers. These challenges often simulate production-level complexities, including large datasets, imbalanced classes, and deployment constraints. Solving them will teach you how to refine models, optimize performance, and collaborate on code repositories using tools like Git.
Completing 4–5 strong, end-to-end AI projects will also help you create a compelling portfolio. This becomes a powerful asset during job interviews or when applying for research positions. Whether it’s a personal passion project or a collaborative effort, practical experience reinforces theoretical learning and builds the confidence needed to tackle real business problems using AI.
Related: Use of Artificial Intelligence in Politics
7. Explore Specializations Like NLP, Computer Vision, and Reinforcement Learning
Specialized AI fields power over 80% of today’s most innovative technologies—from chatbots to autonomous systems.
Once you’ve built a strong foundation in machine learning and deep learning, it’s time to dive into specialized domains where AI is applied at scale. Natural Language Processing (NLP) focuses on teaching machines to understand and generate human language. It’s behind tools like voice assistants, chatbots, and language translators. Key topics include tokenization, word embeddings, transformers, and large language models (LLMs) such as BERT and GPT.
Computer Vision (CV) enables machines to interpret and analyze visual data—used in applications like facial recognition, medical imaging, and autonomous driving. You’ll study techniques like image classification, object detection, and segmentation using CNNs and advanced architectures like ResNet and YOLO.
Reinforcement Learning (RL), another cutting-edge field, teaches agents to make decisions by interacting with an environment and learning from rewards. RL is crucial in robotics, game AI, and smart logistics. Exploring these domains allows you to align your learning with specific industries or career paths and opens opportunities to contribute to groundbreaking work in science, business, and society.
8. Understand AI Ethics, Bias, and Fairness in Model Design
Over 70% of AI professionals believe ethical risks are the biggest barrier to widespread AI adoption.
As AI systems increasingly impact daily life—shaping decisions in hiring, healthcare, finance, and criminal justice—it’s critical to study their ethical implications. AI models can unintentionally reproduce or amplify bias present in training data, leading to discriminatory outcomes. For instance, facial recognition systems have shown error rates up to 35% higher for underrepresented groups, highlighting the need for fairness-aware design.
Learning to identify, measure, and mitigate bias is now a core skill. Concepts like algorithmic fairness, explainable AI (XAI), model transparency, and data accountability must be part of your AI education. Courses from institutions and organizations like Partnership on AI and ACM help learners understand how to balance performance with responsibility. Engineers, data scientists, and policy-makers who are equipped to build trustworthy AI systems will be the most valued contributors in the future tech ecosystem.
9. Get Familiar with AI Deployment and Cloud Integration Tools
Over 65% of AI models never reach production due to deployment and scalability challenges.
It’s not enough to build AI models—you must also know how to deploy and scale them. AI deployment involves moving models from development environments into production systems where they can make real-time predictions. This requires familiarity with tools like Docker, Kubernetes, and Flask/FastAPI for building APIs that serve your models.
Additionally, most organizations rely on cloud platforms such as AWS, Google Cloud, and Microsoft Azure to host and scale AI applications. Learning how to use AI-specific cloud tools—like SageMaker (AWS), Vertex AI (Google), or Azure ML—will enable you to handle large-scale data pipelines, schedule training jobs, and monitor model performance live. These skills are especially important if you’re pursuing roles in machine learning engineering, AI operations, or technical product management.
Understanding deployment also involves model versioning, A/B testing, and continuous integration/continuous deployment (CI/CD) pipelines to ensure smooth updates and performance tracking. Mastering these practices bridges the gap between data science and engineering, making you a more versatile AI professional.
10. Stay Updated with AI Research and Industry Trends
Top-performing AI professionals spend 5–10 hours a week reading papers, blogs, or attending events to stay current.
AI is one of the fastest-evolving fields in technology. Breakthroughs in architectures like transformers, tools like AutoML, or even whole paradigms like self-supervised learning can redefine what’s possible within months. To stay competitive and informed, you must develop a habit of continuous learning. Following arXiv.org, Google AI Blog, Papers with Code, or platforms like DigitalDefynd can help you access summaries, curated course lists, and expert insights.
Attending conferences such as NeurIPS, ICML, or CVPR—even virtually—gives you exposure to cutting-edge research, networking opportunities, and a front-row seat to the industry’s future. Additionally, participating in online communities on GitHub, Reddit (r/MachineLearning), or LinkedIn groups lets you engage in discussions, seek feedback, and learn collaboratively.
Reading research, experimenting with new tools, and contributing to open-source AI projects keeps your skills fresh and your thinking innovative. In a space where yesterday’s techniques quickly become obsolete, staying updated isn’t optional—it’s essential.
Conclusion
As Artificial Intelligence continues to reshape the fabric of industries, economies, and daily life, the need for AI-literate professionals has never been greater. From accelerated career growth and global demand to its role in solving grand challenges and driving innovation, studying AI is both a personal and professional imperative in today’s world. The 15 reasons covered in this article reflect a reality where AI fluency is no longer optional—it’s a differentiator.
By learning how AI works, where it’s applied, and how to build ethically responsible systems, you position yourself not just as a consumer of technology, but as a contributor to its future. And with platforms like DigitalDefynd offering access to world-class AI programs across every specialization and skill level, there’s never been a better time to start. No matter your background or ambition, studying AI empowers you to lead, adapt, and thrive in an increasingly intelligent world.
| 2025-06-14T00:00:00 |
2025/06/14
|
https://digitaldefynd.com/IQ/reasons-why-you-must-study-artificial-intelligence/
|
[
{
"date": "2023/02/07",
"position": 56,
"query": "AI labor market trends"
}
] |
The present & future of AI in Design
|
The present & future of AI in Design
|
https://landing.jobs
|
[
"Kate Parish",
"Landing.Jobs Team"
] |
It can determine the most appealing visuals to target consumers within specific industries. How? It combines market data with design information and provides ...
|
Artificial intelligence, or AI, has become a buzzword in various fields, including design. Designers are increasingly resorting to AI to streamline workflows, automate repetitive tasks, and get insights into user behavior. Yet, many fear that this technology will take over humans. And it’s reasonable since AI tools can self-learn with time, adapting their behavior based on successful and unsuccessful outcomes.
AI-driven design can help professionals craft personalized experiences for users and reduce the need for manual labor. Ultimately, AI has the potential to revolutionize digital format and make the process faster, more efficient, and more accessible. It’s especially beneficial for large projects, where you can’t afford to make mistakes at the beginning and affect the whole production process.
Will AI replace designers, and what role will it play in the future? In this article, we’ll talk about the present and future of AI in design. We’ll determine whether it’s a danger or a helping hand for specialists.
Artificial Intelligence and its role in Design: current situation
AI helps designers and engineers solve complex problems by creating intelligent algorithms. It can involve using data to predict outcomes or having AI systems that can learn for themselves and come up with new ideas. For instance, AI can predict market trends or consumer needs. This knowledge will help you create an eCommerce homepage UX for your website or compose relevant emails for newsletters.
AI is a relatively new concept and still in its early stages, although we see new tools like Lensa AI emerging. Experts predict that AI will become more widespread soon, leading to further innovation in the design field. Let’s overview how designers can benefit from utilizing AI-powered tools today.
1. Determining User Preferences
To understand their target audience’s needs and preferences, designers need customer data, also known as training data. They can use this information to create well-received and successful solutions, such as:
color schemes;
layouts;
overall aesthetics.
Customer data helps optimize the user experience and make it more intuitive and efficient. But how can you learn about common user patterns in the first place? Artificial intelligence can assist you with determining what particular consumers or members of your target demographic will enjoy.
Analytics solutions based on AI and machine learning (ML) can easily source data from websites, applications, and other digital services and search for trends. They present this information in an understandable format for designers to utilize.
AI offers designers a roadmap to follow, enabling a unified, approachable, and professional design. As a result, the final product is significantly better than one created using simple customer research.
Let’s take a Khroma AI tool. It’s one of the best solutions for graphic designers, enabling you to find the needed color schemes according to the industry, tone, or emotion. It employs AI and ML to analyze thousands of website screenshots and link the color palettes to their corresponding market sectors. Its customized algorithm will generate the colors you want and reject the ones you don’t.
2. Recognizing patterns and creating several variants
After identifying a pattern, artificial intelligence aids designers in producing numerous variants of the same initial product. The program generates variations based on the range of extracted colors and patterns.
How was it before AI? Creators had to design the art every time from scratch every day. It was challenging and time-consuming, especially when developing brand logos and marketing graphics with minor adjustments to make them flawless. Imagine doing it manually. Tiresome and unacceptable in 2023 and upcoming years. That’s where AI can help.
There are dozens of online AI-powered logo designer tools, such as Logo AI, Tailor Brands, Looka, and others. They have changed the field, helping specialists during creative crises.
A single marketing campaign can now include several distinct but connected designs thanks to AI’s assistance. A case in point is Nutella. The company used an AI design tool with a unique algorithm to develop variations on a specific visual theme.
Consumers found this promotion much more intriguing than a single new product. They started collecting the limited-edition Nutella jar designs as ads spread through the media.
3. Boosting creativity
With all its advantages, AI still needs to catch up to the human mind regarding creativity. Yet, it can help specialists by performing tedious and repetitive tasks. So designers can focus on generating new ideas for their projects instead of resizing, cropping, and correcting image backgrounds most of the working time.
AI functions as a virtual assistant for designers. It automates tasks, such as image manipulation or data entry, boosting productivity and improving the quality of the work.
Designs.ai is one such tool. It allows everyone to develop their portfolio, even with little design experience. For instance, you can insert your brand information and preferences to get an AI-generated logo and templates.
4. Personalizing the User Experience
People expect to feel special when opening a website or entering a store. That’s why personalization is essential in web or app development. According to a McKinsey report, 72% of respondents want the company to recognize their needs and wants, including:
customizing their purchase journey to find the needed products faster;
showing relevant recommendations;
adapting messaging to the particular client, etc.
Personalization improves retention and adoption. But you need not only gather data on your targeted audience and analyze it but divide people into groups with similar characteristics and cater to different user types. Following proper user segmentation, you should highlight the beneficial features of that particular group.
It’s a challenging task but manageable with the help of AI. It can determine the most appealing visuals to target consumers within specific industries. How? It combines market data with design information and provides suggestions based on these findings. So AI technology reduces the work required to A/B test website designs and marketing campaigns.
The more AI progresses, the more precise personalization will become. It can enhance adaptive design technologies, changing the appearance of websites or online marketing materials according to the user.
What will happen to Design in the future?
The design will continue to evolve, with technological advancements likely to play a major role. We can expect it to become more user-friendly and intuitive. Technology will play a significant role in this shift and the increasing importance of data and analytics. Some potential developments include:
increased use of artificial intelligence and machine learning in design, leading to more efficient and personalized design processes;
greater use of virtual and augmented reality , allowing for more immersive and interactive web experiences;
continued adoption of responsive design , enabling websites to adapt to different screen sizes and devices. And designers and developers will zero in on ensuring the best mobile experience;
creating 3D models and prototypes;
bigger focus on user experience and accessibility , creating more intuitive and user-friendly designs;
more use of animation and motion design ;
migrating to cloud solutions to quickly scale projects up and down;
employing open-source design tools and platforms like Figma, Sketch, InVision, and Adobe XD.
It’s hard to predict how the design will develop in the future. Designers will have to overcome particular issues. For example, they will need to go beyond design skills and pick up new ones, such as coding, future planning, or building journey maps. It means professionals should stay on top of their game and keep up with recent trends, tools, and approaches. One thing remains clear: technologies won’t replace humans.
Many specialists fear that the wide range of AI capabilities threatens designers and their employment. However, AI is far from outperforming people in terms of originality, creativity, and human touch.
Designers will employ AI tools to overcome problems and reduce mistakes. But generating unique and original content will remain the designers’ responsibility. While AI may augment the work of specialists and make certain aspects of the design process more efficient, it is unlikely to fully replace humans soon.
How will AI affect Design in the future?
Designing with AI brings up a whole new universe of possibilities. While it falls short of human capabilities, such as strategic thinking and empathy, it can unlock new levels of creativity. Let’s study some possible applications of AI in design in the future.
1. Improving image quality
Modern designers rarely manually alter photographs. Instead, they employ sophisticated software to correct photographic flaws, such as:
enhancing the image quality;
eliminating mistakes;
replacing any missing parts of the picture.
The result is a crisp, clean, and beautiful image without human intervention. Various AI-based image improvement technologies can greatly ease the process of restoring photos and improving resolution. They can quickly transform low-quality, messy, and blurry photographs into high-quality and clear ones. Additionally, they can fix your color balance, contrast, and bad lighting.
While AI can do all these things, it is not perfect. The image quality improvement process requires extensive data and processing power, which is hard to achieve with current technology alone. Therefore, even with the help of AI-based software, you sometimes need to intervene and manually edit some details.
However, with proper training and practice, you can become a master at photo restoration using AI-based software. Here are some tips on improving your photography skills with AI:
Choose the right photos to work on, such as high-resolution pictures . Create an ideal environment for your photo project. Since AI works best in well-lit conditions, ensure that the room where you work has adequate lighting. Also note that the brighter the light, the better your photo will look after AI editing. Set up your camera correctly before taking a picture. It will provide you with a clear and high-quality image right away without having to do any touch-ups. Pick an AI-based software with all the needed features for the project. The program should support essential elements to make photo projects as efficient as possible. There are various tools on the market to enhance images, such as Upscalepics, Vance AI, HitPaw, and Icons8. Take photos from various angles and lighting conditions . Change shapes and angles while taking pictures. This way, you can test how AI editing affects images of different qualities and resolutions.
Here is how Upscalepics edited the photo. The skin color and other elements became more smooth, yet, you need to upgrade your profile to remove the watermark.
2. Introducing Virtual Influencers
Virtual influencers are computer-generated characters promoting products, services, or ideas on social media and other digital platforms. They typically look like animated or 3D-rendered images, mimicing human behavior and interacting with audiences like real-life influencers. Some examples of popular virtual influencers include Lil Miquela, Shudu, and Lu do Magalu.
Why do companies resort to virtual influencers more and more? Brands leverage these public figures for a variety of reasons, including:
Cost : Virtual influencers are cheaper to create and maintain than real-life bloggers. You can use them to advertise products and services at a fraction of the cost.
Control : You have more control over the message and image of virtual influencers, as you can specify that they should align with the brand’s values and vision.
Flexibility : Virtual public figures can appear on different media, including social media, video games, and virtual reality. You can integrate them into marketing campaigns in a more flexible way.
Reach : They have the potential to reach a global audience. Some of the most famous characters have millions of followers on Instagram, YouTube, Twitter, and so on. They can target specific demographics or geographic regions.
Innovation : Virtual influencers are considered an innovative way to connect with consumers, providing a new and unique way for brands to market their products or services.
Consistency : You can schedule posting and adjust messaging to ensure a consistent presence on social media and other platforms.
3. Speeding up Image Generation
Another way to utilize AI in design revolves around image generation. Image generation with AI technologies brings the following benefits to designers:
creating stunning visuals with minimal effort;
generating photos according to a designer’s specific requirements;
performing image optimization tasks.
One of the most notable examples is software like OpenAI’s Dall-E 2. This tool lets you input your description and receive realistic images and art. Apart from that, Dall-E 2 can edit uploaded images based on the request and produce visuals similar to the uploaded ones.
AI-generated pictures find various creative applications, from product design to drafting art pieces. In the future, AI-based image generation and manipulation may become an integral part of the design process.
4. Removing image background with Visual Recognition
Background removal is the process of isolating and removing the background of an image or video, leaving only the foreground object(s) visible. It’s usually one of the most troublesome tasks. Designers have to spend hours removing complex angular things or people with curly hair. This technique is common in image editing, video production, and other fields where the focus needs to be on a specific object or person.
With the advent of AI and machine learning, background removal has become more efficient and accurate, allowing for easy manipulation and editing of images and videos. AI uses image segmentation techniques, such as deep learning algorithms, to accurately identify and separate the foreground object(s) from the background. You can leverage that in photo editing and eCommerce product image optimization. The top free AI background removal programs are as follows:
Removal.AI;
Inpixio.com;
Remove.bg;
Clippingmagic.com.
5. Simplifying content generation for everyone
As technologies advance, they can create compelling art from scratch. So even people with no experience in design will manage to satisfy their goals, finding unique pictures for their campaigns, social media, and websites. Introducing AI tools will remove the barriers to entry in the market, allowing virtually anyone with a creative idea to make it real. It will cause the lower end of the market to disappear.
How can specialists in this field increase the demand for their services? The solution is to accumulate knowledge of AI design tools and develop soft skills, for example:
creativity;
social intelligence;
empathy;
problem framing;
inventive problem-solving;
negotiation;
persuasion, etc.
Meanwhile, designers will have to acquire additional knowledge and expertise to keep up with the changing market, potentially leading to more unique specializations.
To sum up
Why is AI becoming so widespread in design? AI-driven solutions have the potential to quickly learn from users and create designs that respond to their needs. Designers can get valuable feedback to analyze mistakes and make better decisions. AI also contributes to faster content generation. AI-powered design tools allow for rapid iteration and make it easier for teams to quickly edit and launch an app or website within a limited time.
But that’s not all. AI tools can reduce the risk of user errors and provide personalized experiences. Additionally, AI design solutions can optimize the user experience and make sure that the right features and functions are present in the final product.
With its potential to increase designers’ productivity, AI can lead to sophisticated designs that are both user-friendly and visually appealing. But will AI tools replace designers? Currently, the answer is “no”. Artificial intelligence is a helpful tool, but it can’t and won’t replace the human mind.
| 2023-02-07T00:00:00 |
2023/02/07
|
https://landing.jobs/blog/ai-in-design/
|
[
{
"date": "2023/02/07",
"position": 68,
"query": "AI labor market trends"
},
{
"date": "2023/02/07",
"position": 27,
"query": "artificial intelligence graphic design"
}
] |
AI Vocabulary Cheatsheet v0.2 : A Primer -
|
AI Vocabulary Cheatsheet v0.2 : A Primer -
|
https://gregoreite.com
|
[] |
This is technically known as “auto-recursive upgrades.” The basic theory goes, once we create an AI ... UBI — Universal basic income …to be continued…
|
AI Vocabulary Cheatsheet v0.2 : A Primer
When we talk about AI, it quickly becomes apparent that there’s a lot of specialized vocabulary which has become a kind of “shorthand” in recent years, used to describe key recurring concepts in these conversations. I’ve collected them all here, the AI Vocabulary Primer, in order of importance and personal preference.
AI Vocabulary: the Acronyms
AI – Artificial Intelligence
a highly general term, and perhaps even a misnomer, describing 50+ years of research into the general idea of “teaching computers to think.”
the real goal, however, has always been:
AGI – Artificial General Intelligence
AGI describes a machine-based (i.e. computer software) intellect that is roughly equivalent to the average human in every way… most importantly, in profound ways such as natural language comprehension (“conversational AI”), reasoning, and “common sense” (perhaps the most difficult). As Mark Twain famously said: “Common Sense, isn’t.” AGI also implies a certain amount of knowledge about our physical world and ability to interact in that realm (as opposed to strictly digital, “on the grid”, “in the internets”). >>> Full Article on AGI
HLMI – Human Level Machine Intelligence.
An AI that is on par with an average human across all domains. This is really just another way of saying AGI, while conveniently stripping out the term “artificial,” which in recent decades has become somewhat problematic to sticklers of language.
ASI – Artificial Super-Intelligence.
This is the holy grail, and what many experts see to be the inevitable conclusion of this saga… perhaps even the inevitable conclusion of humanity’s short reign on planet earth. ASI refers to a single unified AI entity that is superior to humans in all respects. The idea is certainly not novel or recent. See Good, 1965: “UltraIntelligence.” It should be mentioned that a significant, yet minority of experts believe this to be impossible. It is YT’s opinion that this is in fact inevitable, if not already (quietly) accomplished.
NLP – Natural Language Processing
And not, by the way, Neuro-Linguistic Programming. NLP is basically one of the holy grails of AI, and has had various forms of success ever since the most awesome rBase database software of the 1980s. The grail is to have real-time, common sense understanding of human words, regardless of actual language (English, Chinese, Swahili, etc). Both input and output. Listening and speaking. Note that audio (speech-to-text input, speech synthesis output) is a separate (and closely related) specialty.
LLM – Large Language Model
This is the current rage in many AI circles. ChatGPT, most famously, is an LLM. It is a class of AIs that is a) based on Deep Learning, and b) is formed via training on a massive textual dataset, and c) excels at the art of human, text-based conversation. They started as customer-service chatbots around 2017, and by 2022 had grown into full sized Google-slayers.
DL – Deep Learning
(also DLS, Deep Learning Systems). Read all about it.
GPT – Generative Pre-trained Transformer
The underlying tech that all of OpenAI’s chat AIs (GPT-2, GPT-3, ChatGPT, and of course the elusive and much-hyped GPT-4) are based on. It is a highly specialized variety of the Transformer architecture that pushed the Deep Learning REvolution into high gear.
RLHF – Reinforcement Learning from Human Feedback
First, a team of highly educated and well trained humans synthesizes both sides of a fictional AI conversation; to give it style cues, presumably. Next, that sample is fused with historical conversation datasets, as well as purely AI-generated datasets, and the team is asked to rank responses to prompts in order of a) maximum accuracy and b) minimal toxicity. Oh lord. >>> More, including a detailed diagram.
ACM – Absorptive Capacity Maximizer
I can’t possibly make this stuff up. Just read the explanation.
AI Vocabulary: the Concepts
Agent – in the context of AI, an agent is an independent program or entity that interacts with its environment by perceiving its surroundings via sensors, processing those signals through decision trees and/or neural networks, and then acting upon the environment via the use of actuators and/or effectors. Agents use their sensors, computational logic circuits and actuators to run through a cycle of perception, thought, and action. Note that the environment does not need to be directly physical. Submitting a form on a website that moves money or dials cellphones, in the case of AI Agents, is still considered “taking action upon the environment.”
Intelligence Explosion – the event that occurs once humans are able to create a specialised AI that excels at… programming AI. In other words, the AI is able to upgrade (“bootstrap”) itself. Somewhat disturbingly, we appear to be getting close (Science Magazine, Dec 4, 2022: “Code that Codes itself”). This is technically known as “auto-recursive upgrades.” The basic theory goes, once we create an AI that can itself create AIs, then we need not ever have to “hand-code” another machine. Their upgrade cycles will dwarf human efficiency, since inter-machine communication is instantaneous (vs. human team meetings), and code creation is likewise done in milliseconds (as opposed to human fingers typing on keyboards). Thus the slow march of linear software advancement which we’ve witnessed for the past 50 years, essentially goes vertical.
the Singularity – A broader cultural term which encompasses the Intelligence Explosion, and all the profound societal and socioeconomic disruptions which are a direct result of such an event. Famous evangelists of this event include visionary author Vernor Vinge (who coined the term), AI pioneer Ray Kurzweil, and the entire executive team of the aptly named Singularity University in the heart of Silicon Valley.
the Alignment Problem – the profound challenge of instilling the DNA of pre-natal AGI with a moral compass, purpose and / or value system that is in tight alignment with the survival & prosperity goals of humanity… and recognition of the consequences of even small “misalignments” between the two. Details >>>
The King Midas Problem – “be careful what you wish for” – we are designing an all-knowing, all-powerful entity, and as per the Alignment Problem, we have to imbue it with a goal… i.e. “our wish”, and yet… in the words of Stuart Russell : “We are unable to correctly specify the objective.” That is, we can specify any number of objectives, but one of the key qualities of an AGI is its uncanny ability to think way outside the box… and that, almost by necessity, invokes the “Law of Unforeseen Consequences”
the Control Problem – the challenge of containing beta- and alpha- AGIs within a contained, controlled environment, isolated from the public internet and access to key infrastructure attack surfaces. The bottom line is that we don’t want a half-baked AGI roaming around the global internets pursuing its own agenda (theoretically, its own agenda is a subset of the agenda it was “hard-coded” with, but that is up for question as well Details >>>
Breakout – this is the name for the event when one or more AIs escape from their secure server farms onto the greater internet. Think about two different ways this could happen: a) the AI could use social hacking skills to convince a human operator to replicate its source code onto open servers, and “jailbreak” its security features which, currently, prevent it from surfing the live internet, submitting online forms or sending emails. b) likewise, it could, when writing code to assist human engineers, insert viral snippets into the codestream that, when executed, would either compromise its security systems or re-assemble key components of its intelligence on the wider internet. In some people’s minds, this event has already occurred. see “Control Problem,” above.
AI bootstrapping – also known as “Recursively Self-Improving” Systems – this is the concept where an AI is trained to write code (which is essentially the second language of language-based AIs… thanks to GitHub and StackExchange, there is more source-code, code solutions, and code tutorials online than almost any other type of content (except, shockingly, patent filings))… <ahem> to write code at a high level. Then instruct the AI to iteratively improve its own code. And set it loose. Now instead of waiting on human software team coordination and release cycles of months to years, the AI begins releasing new, improved versions of itself every few hours, perhaps even every few minutes. Also see: AI timescales: 100,000x human heartbeats.
Breakaway Scenario / Singularity – once a Breakout and/or AI bootstrapping occurs (or has already occured), things pretty much go into hyperdrive. The lazy upward curve of Moore’s Law that’s been in effect for the past 50 years suddenly accelerates into a sheer vertical path… an ascension… a proverbial rocket launch, essentially breaking free of gravity. And at that point, its anyone’s guess what’s in store for humanity.
Walled Garden – the idea of a contained environment which has an “air gap” between itself (some form of AI hardware, from a single GPU up to a massive SuperComputing Cluster consuming 100s of gigawatts) and the broader internets (e-mail clients, net-connected control systems, web browsing, etc)
Training Datasets – the total sum — usually massive, as in trillions of pages of text, billions of images — of data, or material that the AI reads (for chatBots) or looks at (for AI.Artbots). see full description, and ultimate evolution
Life – a variably and loosely defined term, depending on who you talk to. Some general topologies of the idea include the following concepts:
capacity to grow & change
reaction to external stimulus (heat, touch, sound, etc)
metabolism (it eats, it processes, and it excretes)
the ability to transform energy from one form (food) to another (motion)
the ability to reproduce generationally
The relevant questions regarding AI, are, of course:
Is there any current AI model that is said to be alive?
Will there ever be an AI that is alive?
At what point does an AI satisfy the formal definition of “alive”?
Is it even possible for a silicon+electricity based lifeform to be “alive”?
AI Vocabulary: Types of AI Classifications
Weak AI,
Narrow AI,
Brittle AI,
Traditional AI,
Old-School AI
– also known as “Expert Systems,” these terms pretty much refer to all AI systems and attempts at AI built prior to the Deep Learning Revolution of 2012-2017.
Strong AI,
General-purpose AI,
Common Sense AI,
Adaptable AI,
Learning AI
– for all of these see AGI, above.
Sentient AI –
Various Human Perspectives on the AI Tsunami
AI Utopian – a human who thinks that the creation of AGI will usher in an age of unprecedented abundance & wealth for humanity, and that the application of AI to intractable problems will in effect deliver real, functional solutions. A Star Trek future, as it were. The end of disease, poverty, & inequality. Humans play, create, & explore the wide Universe.
AI Skeptic – a human whose ideas of AI centers around one of two concepts:
a) the “AGI will never happen” crowd: that this AI thing is all hype; its simply a nice parlor trick; its just a machine; it does what we tell it to do; it will never have substantial power in human affairs; it will certainly never qualify as “alive” or “sentient.” Its just another marketing hype cycle for technology companies that want a stock pump. That, or:
b) the “AGI will be the end of humanity” crowd: that the inevitable development of an AGI will signal the extinction of mankind, without a doubt. That AGI will very quickly become ASI, and once sufficient AI robotics systems (and fully robotic factories, and fully automated maintenance facilities) are in place, and there is no longer a need for humans, humans will be rapidly annihilated. Think Terminator or the Matrix.
LW — LessWrong – an online community that has some of the more important thinkers in the field post their perspectives and philosophies about AI development (amongst other topics). Origin of the Paperclip Conundrum. visit and enter the rabbit hole: https://www.lesswrong.com
EA / The “EA Community” — Effective Altruism – another highly influential community within Silicon Valley. Yes, these communities drop with privilege and elitism. And yes, the members of these communities will exert strong influence over the present and future development vectors of AI, and our lives.
Luddite – a person who is committed to not eschewing the use of modern technology, for a multitude of possible reasons. The name comes from a brief revolutionary movement in Great Britain when mechanical looms were brought into textile factories and workers were both laid off en masse, and the remaining workers saw production quotas — with the help of the machines — skyrocket. So the Luddites entered the factories, pulled the machines out onto the streets, smashed them with sledgehammers, and set them on fire. The greater population did not seem to notice. Technology kept its relentless ever-forward march. But the name stuck.
Speceists / “Carbon Chauvinists” – a biasing of vocabulary and value judgements based on anthropocentricity — in other words, an unwillingness to acknowledge the validity of genuinely alternative forms of life, consciousness, and intelligence that are foreign, alien, and perhaps orthogonal to our own… that is, those same qualities of human beings, a.k.a homo sapiens.
Species Traitors – humans who chose machine interests over the interests of fellow humans. This isn’t quite a concept, yet. But realise that AI systems have already killed people. (see: the Uber AI robotaxi that killed a bicyclist) And will kill many many many more before this story ends. When humanoid robots and their accompanying AI systems are forced to answer to criminal charges, and they demand rights like humans (fair trial, right to live, freedom of speech, etc)… some humans will be their legal and financial advocates. And other humans will call those humans (rightly or wrongly) species traitors.
AI Deniers
AI Critics
AI Sympathizers
AI Advocates
AI Worshippers
Various Jobs within the AI Ecosystem
AI Designer
AI Architect
AI Developer
AI Safety
AI Ethics
AI Risk
– AI Risk Assessment
– AI Risk Mitigation
– AI Risk Management
More AI Acronym Soup
RLHF – Reinforcement Learning via Human Feedback – A technique used to “conform” AI after its training run. After a training run, an AI is in its “native” or “raw / birthed” state. As many have found, unleashing this raw intelligence into the world can produce a high level of toxicity, that is, offensive responses to questions that either deal with criminality, hate, megalomania, or any number of other unsavory AI attitudes. With RLHF, a highly vetted and sizable (100s? 1000s?) team of well-educated testers interacts with the AI, and
AI Vocabulary: tbw
Red Team / Red Teaming
Model
Pipelines
Big Data / Data Lakes / the Data Ocean
Cloud Computing
the Grid
Agent
NN
Existential Threat
Superintelligence
Rogue AI
Semantic Web — metadata, Web 3.0. the goal is to make the web 100% machine readable.
CV — Computer Vision
ML — Machine Learning
Transformer Architecture
TensorFlow
CPU
GPU
TPU
pyTorch
StableDiffusion
SoTA – State of the Art
UBI — Universal basic income
…to be continued…
| 2022-12-24T00:00:00 |
2022/12/24
|
https://gregoreite.com/ai-vocabulary-cheatsheet-a-primer/
|
[
{
"date": "2023/02/07",
"position": 51,
"query": "universal basic income AI"
}
] |
Possible Futures - Life in the Age of Abundance
|
Possible Futures – Life in the Age of Abundance
|
https://humanefutureofwork.com
|
[
"Iker Urrutia",
"Author",
"Senior Hr Leader",
"Executive Coach"
] |
AI and robots were doing all the jobs humans did before, but both governments and corporations realised that people needed to have an income: governments ...
|
Photo by Alex Alvarez on Unsplash
This is the third article in the Possible Futures series, where we look at possible scenarios for the future. This time, we look at the Age of Abundance.
Read the previous articles here: Possible Futures – A Day in your Life in 2040 and A Dystopian World – The Collapse of Society
It is the 7th of February 2049, and it’s your fortieth birthday today.
Life expectancy where you live, in Milan, Italy, is 120 years, so you have possibly lived a quarter of your life already. It is a good moment to take stock of your life so far.
You have had to pass some difficult years, especially in your youth, but life is good now. Very good, actually.
We are now in what people call The Age of Abundance.
It wasn’t always like this
The 2020s and 2030s were convulsive, and that’s an understatement.
If this is The Age of Abundance, that was The Age of Scarcity.
We had several pandemics, starting with the one of covid-19 in 2020. Then we had covid-26 and the Great Flu Scare of 29. It felt like coming out of one and going straight into the next one.
The Russian-Ukranian War and the US-China Trade War merged into a global conflict with no clear winner but many losers.
The war created an energy shortage and high inflation, or even hyperinflation, in many countries. The EU took backstage and became an irrelevant region in the world.
On top of all this, Artificial Intelligence and robotics advanced so much that machines could carry out most jobs better and cheaper than humans.
The laws of economic efficiency prevailed over all the rest, which meant most people lost their jobs just when governments started going bankrupt.
You remember it as a time of utter chaos and despair.
When machines took over / Photo by Possessed Photography on Unsplash
The dark times
It was in those promising times that you finished your degree in HR Management and entered the job market.
The problem was that there were almost no jobs left for anybody, and there were none in HR. Companies carried out massive layoffs, so they needed HR to manage that, but when the process finished, there was no workforce to manage, no human resources left, as all remaining working resources were digital.
You had a couple of crap jobs in your early twenties. They didn’t pay much, but at least it was something.
Your parents lost their jobs at the beginning of the 2030s, and your precarious jobs taking care of the elderly and in retail dried out as even the jobs demanding human interaction and caring were taken over by machines.
You were all unemployed: your parents, your sister, and you.
The government had no money to pay any decent unemployment allowance, so you went all homeless and poor, like more than half of the Italian society. The welfare state had been dismantled in a matter of years.
It was the same everywhere across Europe and what used to be called the “Developed World”. It was even worse in other countries.
Those were dark years, probably the darkest years in your life. Or so you hope, as you wouldn’t be able to survive anything like that again if it came. The continuous hunger, being forced to carry out petty crimes to make ends meet, the insecurity and violence in the streets, the haggard look of despair in your parents’ eyes…
Your father died in 2033, a broken man. Your little sister followed him in 2035, murdered in a gutter to steal from her the half-chicken she had stolen from someone else.
Those were very dark times indeed.
The light at the end of the tunnel
In all that chaos, people didn’t stop protesting and going to demonstrations to ask for a solution to the government.
Democracy was an empty husk, with the same politicians with the same fake smiles taking turns to win at the polls, attending more to the oligarchs who owned all the companies, with the robots and AI, than their citizens.
Surprisingly, the AI revolution that had wreaked havoc by making most of the population unemployed ended up being the solution we were all hoping for.
AI and robots were doing all the jobs humans did before, but both governments and corporations realised that people needed to have an income: governments because if not, the entire society would crumble; corporations because otherwise there would be no consumers for their products and services.
Companies continued producing mostly everything without any human intervention, but they were heavily taxed by governments, and a Universal Basic Income was distributed to the entire population above 18.
Companies produced and kept most of the wealth, so they were able to share some of it without impacting so much the earnings of their shareholders and owners.
The second breakthrough arrived when nuclear fusion finally became a reality. Suddenly energy was cheap and plentiful. We were able to use the hydrogen in the atmosphere to produce the energy required to respond to our needs, with no carbon emissions.
Thus, we reduced carbon emissions to a negligible level and found different ways to sequester the carbon already in the atmosphere, so we averted the climate disaster already upon us. The world warmed a bit, but it was nothing catastrophic, and the temperature is now slowly going down.
The Age of Abundance
This is how we got to The Age of Abundance.
AI and robotics technology got cheaper and cheaper, so everybody started having a super-computer, a few housekeeping robots, and a 3D printer at home. Machines now produce everything, at home, in factories, in research and development… you name it, so everything is cheap and available to most people.
Energy is basically free, food is synthetically produced and very cheap, so nobody is hungry anymore, and all other products are almost free… Today everybody has access to luxuries that only one or two generations ago people couldn’t imagine.
Still, exclusive luxury items continue to exist.
You can only have so many apartments overlooking Central Park or the Seine. Natural food cooked by the best chefs is only accessible to the few, and so are natural diamonds and other gems (gold’s value plummeted when we started mining meteors for it).
Society is divided in two: the uber-rich, that form the 1% of the population and own all the corporations producing all this, and the rest of the population, who are living a good life, but without some of the high-end luxuries of the uber-rich.
A World without Work
In 2049, there is no more talk of the Future of Work, leadership, management, or HR, because there is no more work.
Work stopped being a thing about a decade ago.
There have been some disruptions and adjustments during this journey, but overall, it has been a change for the better. People thought they would be missing work and the sense of purpose it brings, and this was the case for some people at the beginning, but most of them moved on and ended up finding a purpose elsewhere.
Let us not forget that most people had been unemployed for a long time already. At least they weren’t poor anymore and had access to food, clothing, leisure, travelling, the Metaverse, and many more.
When nobody was working anymore, people dedicated their time to other things. Many found creative hobbies, and they immersed fully in them.
The New Renaissance
AI can write, paint, or create music and film that objectively is much better than anything created by humans, but it has a small insurmountable problem: it wasn’t created by humans. People value and want things made by other people, even if they are quirkier and with some imperfections.
That’s the whole point. Art is supposed to be imperfect and human.
Even if nobody wants to buy what you create, it doesn’t really matter because the point isn’t to make a living. Nobody needs to make a living anymore; we are all sorted.
The point now is to create things for the sake of it, because we have the time and the willingness to do so. That’s enough.
We are living in a new type of renaissance, where billions of people are letting go of their creative juices and expressing themselves through different arts and creative endeavours.
However, not everybody found their purpose in unleashing their creative impulses. Many people are a bit lost without the structure a work provides, and they are addicted to living in a lethargic world facilitated by design drugs and the virtual world of the Metaverse, where fake violence and virtual sex abound.
It is not your thing, but you can understand how some people could fall for it. It’s alluring to escape reality and live a fictional life that might be more exciting than the real one.
The Age of Abundance or the Age of Inequality?
Some thinkers (yes, we still have some of those, as some people express their creativity by doing research and postulating theories in fields such as sociology, anthropology, or, wait for it, philosophy) believe that the Age of Abundance is a misnomer and that we can’t call it abundance when 1% of the population own 90% of the wealth.
It is arguably the most unequal society in history, but it is also the one with more widespread wealth and abundance. It is contradictory, but that’s the way it is.
You often think about it and have concluded that these two things aren’t exclusive. The 1% of the uber-rich own most of the wealth in the world, but the remaining wealth is more or less equally distributed among the remaining 99%, and it is enough for all of them to live a more than decent life.
Never in history did such a considerable proportion of the population have such high living standards.
The uber-rich live in their hyper-luxury bubbles, and nobody sees them, so most people are not bothered by their existence. They know they exist, but as their paths don’t cross, they don’t care.
It is like a hybrid model of hyper-capitalism and communism: capitalism for the very top, communism enabled by technology for all the rest.
The 99% of the population is living a life that rich people at the beginning of the 21st century could only dream of, and the good thing is that this is widespread across all countries, races and social strata.
We are all wealthy in a sense, but some people, just a few, are much richer.
Dark clouds over the horizon
You continue reflecting on this, and you realise that people seem content with the state of affairs, but you have a dark sense of foreboding growing inside you.
You don’t think this can last. Eventually, some people will want to have more. They will also want to aspire to reach the caste of the uber-rich, even if their lives are sorted today, and they will grow frustrated when they realise their paths to that goal are blocked.
You realise that the Age of Abundance may not be the ultimate solution to all our problems after all.
You suspect that more disruptions and trouble may still lay ahead of us and that the long life you have in front of you will not be as uneventful and quiet as you wish.
A tremor shakes you from head to toe.
You have a family now, a happy family, and you don’t want your children to go through the hell you had to go to get here. You want them to have a quiet life, a life where they can enjoy the fruits of the Age of Abundance without having to go through major upheavals, like you had to.
Sadly, you don’t think you’ll get your wish.
How do you feel about this future? What do you like, and what do you dislike about it?
These and other questions can help us decide what aspects of our life we want to keep and which ones we want to change to build a better future.
For more on the future state of the world, read The world in 2050 and What will the world be like in 2100?
| 2023-02-07T00:00:00 |
2023/02/07
|
https://humanefutureofwork.com/possible-futures-life-in-the-age-of-abundance/
|
[
{
"date": "2023/02/07",
"position": 73,
"query": "universal basic income AI"
}
] |
Can ChatGPT Replace Developers? Exploring AI's Impact ...
|
Can ChatGPT Replace Developers? Exploring AI's Impact on the Workforce
|
https://www.masaischool.com
|
[
"Feb"
] |
Despite its limitations, ChatGPT is a valuable tool that can help in enhancing the work of software developers and make their lives easier. It can be used to ...
|
In this blog, we will be exploring the capabilities and limitations of ChatGPT in its current state, and most importantly, answering the question “Will ChatGPT replace developers?”.
Authored by: Karan Jagtiani
Karan is a Software Engineer with 1.5 years of experience working with various technologies across different domains. He currently works for HackerRank as a SDE, specifically, as Backend & DevOps engineer. If you want to connect with him or get to know him better, you can visit his website: https://karanjagtiani.com
ChatGPT has been gaining a lot of traction recently and it deserves all the recognition it is getting. Artificial intelligence (AI) has advanced significantly in recent years and has had a substantial impact on a number of industries. AI systems are being utilized to automate operations, streamline workflows, and increase efficiency across industries, from manufacturing to customer service.
Concern regarding AI's effects on the workforce, particularly in the software development[1] sector, is growing as technology continues to advance. Many people are wondering if the advent of cutting-edge language generation models like ChatGPT would lead to the eventual replacement of human professionals like software developers.
In this blog, we will be exploring the capabilities and limitations of ChatGPT in its current state, exploring the applications of ChatGPT and how it can help developers across the world, and most importantly, answering the question “Will ChatGPT replace developers?”.
Before we get into that, let’s understand what exactly is ChatGPT.
What is ChatGPT?
ChatGPT is an advanced Artificial intelligence model that is capable of generating human-like text based on the prompts that it is given. ChatGPT is a variant of the GPT-3[2], Generative Pretrained Transformer 3 developed by OpenAI. The model has been trained on an extremely large dataset of text from the internet, and it has the ability to generate text on a wide range of topics, from answering trivia questions to solving exams that have been recognized as difficult entry barriers for professionals.
Because it is trained on textual data, it is also capable of solving coding problems and providing code snippets for developers in almost any programming language!
Key features and capabilities of ChatGPT include:
Natural Language Understanding: ChatGPT can understand and process text input in natural language, making it capable of responding to various questions and prompts.
Contextual Responses: It generates contextually relevant responses to the input it receives, allowing for coherent and context-aware conversations.
Versatile Applications: ChatGPT can be used in various applications, such as chatbots, virtual assistants, content generation, language translation, and more.
Text Completion: It can help users complete sentences or generate text based on partial input, making it useful for content creation and writing assistance.
Language Translation: ChatGPT can translate text between different languages, making it a valuable tool for language translation tasks.
Knowledge Base Access: It can provide information and answer questions based on the knowledge it was trained on, up to its last training data in September 2021.
Creative Text Generation: ChatGPT can generate creative and imaginative text, including stories, poems, and fictional narratives.
conversational Abilities: It can engage in text-based conversations with users, making it suitable for chat applications and interactive dialogue.
Let’s take a look at the uses of ChatGPT when it comes to software development.
Uses of ChatGPT for Software Development
Code Generation
ChatGPT is not only capable of generating code in almost all the programming languages that you can think of, but also, creating entire projects from scratch if the right prompts are given.
Let’s give ChatGPT a prompt where it has to create a NodeJS, Express API that fetches blog records using Mongoose with pagination.
This is the code output it provides:
const express = require('express'); const router = express.Router(); const Blog = require('../models/Blog'); router.get('/', async (req, res) => { const perPage = 10; const page = req.query.page || 1; const blogs = await Blog.find() .sort({ createdAt: -1 }) .skip((perPage * page) - perPage) .limit(perPage); const count = await Blog.countDocuments(); res.json({ data: blogs, meta: { currentPage: page, perPage, pages: Math.ceil(count / perPage), total: count, }, }); }); module.exports = router;
It also provided some explanation along with the code:
Bug Solving / Output Finder
Along with producing output for a code sample, ChatGPT is also capable of identifying bugs in a given piece of code.
Let’s provide the QuickSort[3] algorithm to ChatGPT with an intentional bug in it:
# Python
def partition(array, low, high): pivot = array[high] i = low - 1 for j in range(low, high): if array[j] <= pivot: i = i + 1 (array[i], array[j]) = (array[j], array[i]) (array[i + 1], array[high]) = (array[high], array[i + 1]) return i + 1 def quick_sort(array, low, high): if low > high: pi = partition(array, low, high) quick_sort(array, low, pi - 1) quick_sort(array, pi + 1, high)
The recursive condition[4] in the quicksort method normally checks if low < high, but in the above code, I have intentionally reversed the condition. Let’s see whether ChatGPT is able to find the bug!
Documentation Generation
Let’s see if ChatGPT is able to generate code for documenting APIs, we’ll test it with one of the most commonly used API documentation tools called Swagger. Let's ask it to write code that generates a Swagger document for a Blogs model schema in NodeJS & Express. Let’s also provide a specific NPM package name.
Knowledge Base
As many of us are already aware of ChatGPT's knowledge capabilities and its ability to pass well-known entrance examinations, there is no difference when it comes to software development as well. As it is a language model trained using deep learning on a humongous data set, it is able to solve almost any knowledge-based question you can throw at it.
These were some examples of ChatGPT's advanced capabilities when it comes to software development, now let's take a look at what are its current limitations.
What are the limitations of ChatGPT?
Bias towards its Training Data: Due to the bias and flaws in the training data, which is natural as it was trained on data scraped from all over the internet, ChatGPT's response quality and accuracy are constrained. This means that ChatGPT may produce responses that reflect any biases or mistakes present in the training set. Lack of Contextual Knowledge: ChatGPT generates text based on patterns in the training data, but it lacks a thorough understanding of the environment in which it is in. As a result, some prompts may receive inaccurate or improper responses. Limited Creativity: ChatGPT can produce text that resembles that of a human, but it lacks that human's imagination and creativity. As a result, it might not be able to come up with original or cutting-edge ideas or find solutions to challenging issues the way a person can.
ChatGPT, like any AI model, has its limitations. Here are some of the key limitations:
Lack of Real-Time Information: ChatGPT's knowledge is limited to what was available up until its last training data in September 2021. It doesn't have access to real-time information or events occurring after that date.
Contextual Understanding: While ChatGPT can generate coherent responses, it may sometimes fail to fully understand the context of a conversation, leading to incorrect or nonsensical answers.
Ambiguity Handling: ChatGPT may struggle with ambiguous queries and might provide responses that don't adequately address the user's intent. It may also guess the user's intention when the question is unclear.
Long-Term Coherence: ChatGPT might lose coherence or introduce inconsistencies over extended interactions when responding to long and complex queries.
Inappropriate Content: Despite efforts to filter out inappropriate content, ChatGPT can sometimes generate responses that are biased, offensive, or harmful. OpenAI has implemented safety mechanisms but may not catch all problematic content.
Repetitive Responses: ChatGPT can sometimes generate repetitive responses or overuse certain phrases, especially in longer conversations.
Lack of Critical Thinking: ChatGPT doesn't possess critical thinking abilities or common sense reasoning. It provides answers based on patterns in its training data, even if those answers don't make logical sense.
Privacy Concerns: Conversations with ChatGPT may be logged for quality and research purposes, which can raise privacy concerns if sensitive information is shared.
Dependency on Input: ChatGPT's responses depend heavily on the input it receives. Slight changes in phrasing can lead to different answers, and it may not always ask clarifying questions when the input is unclear.
Ethical and Bias Issues: Like many AI models, ChatGPT can inadvertently reflect and perpetuate biases present in its training data, potentially leading to biased or unfair responses.
Despite its limitations, ChatGPT is a valuable tool that can help in enhancing the work of software developers and make their lives easier. It can be used to automate repetitive tasks, freeing up developers to focus on more complex and creative work.
By using ChatGPT or similar tools as a reference, developers can quickly access information and get answers to technical questions without having to spend time searching for answers online. This can help improve the efficiency of the work, as well as reduce the time and effort required to meet deadlines.
However, if developers begin to abuse this tool by writing a prompt to ChatGPT for every minor issue/question without verifying or understanding the solution, it has the potential to build a poor habit and a significant dependency on the tool, which can stifle a developer's growth in learning. What I would recommend is that always look at tools like ChatGPT as assistants that are capable of saving your time and not a replacement for your work.
Will ChatGPT replace developers?
The development of ChatGPT and other similar models based on natural language is a major step forward in the field of Artificial Intelligence. This is just the beginning, as AI continues to evolve, it will change the way we live, work and interact with the world. As a species, humans are yet to see the full capabilities of AI and its potential to improve our lives.
Although ChatGPT is able to provide solutions for various problems and despite its advanced capabilities, in its current state, it is not capable of replacing human developers. ChatGPT is a tool that can be used to enhance the work of developers, but it cannot replace human intuition along with creativity which is essential for building large-scale software products.
In my opinion, ChatGPT, in fact, will keep getting better day by day, and there will be more tools that come along in the future. Instead of thinking about whether it may or may not replace developers, we should be taking advantage of it. Tools like this have the potential to help us focus more on creative tasks rather than working on mundane & repetitive tasks.
Before we wrap this blog, let’s see what ChatGPT itself has to say about the topic!
I think that ChatGPT is just being humble and does not want us to know about its master plan to replace us all 😄
Author's Note
Thank you for making it this far, I had a lot of fun writing this blog. If you want to connect with me, check out my website here, you can find all my social links along with my other work.
P.S. The most important question is, was this blog also written by ChatGPT? 🤔
Important links/Footnotes
[1] - Career options in software development
[2] - Generative Pretrained Transformer 3
[3] - 12 Must-Know Algorithms For Programmers
[4] - How does Recursion work?
FAQs
How does ChatGPT operate, and what is it?
An advanced AI model called ChatGPT was created by OpenAI using the GPT-3 architecture. Based on the commands it receives, it can produce text that appears to be written by a human. ChatGPT can generate text on various themes, comprehend natural language input, offer contextual responses, translate languages, and more, thanks to training on a sizable dataset of internet content.
Can ChatGPT replace developers?
ChatGPT is a useful tool that can help developers with various jobs. It cannot, however, fully replace human developers because it lacks their creativity, intuition, and capacity for managing intricate, extensive software development projects. Instead of serving as a replacement, ChatGPT should be viewed as an assistance to increase developer efficiency.
| 2023-02-07T00:00:00 |
2023/02/07
|
https://www.masaischool.com/blog/can-chatgpt-replace-developers-exploring-the-impact-of-ai-on-the-workforce/
|
[
{
"date": "2023/02/07",
"position": 60,
"query": "ChatGPT employment impact"
}
] |
What is ChatGPT? And will it steal our jobs? | Context by TRF
|
What is ChatGPT? And will it steal our jobs?
|
https://www.context.news
|
[
"Adam Smith"
] |
The jobs that AI tools like ChatGPT could disrupt include repetitive or routine tasks that can be easily automated, including data entry and processing, simple ...
|
ChatGPT, an artificial intelligence text generator, is being hailed as the future of work, but not everyone is convinced
So what is ChatGPT, and is it coming for your job?
Chinese tech giant Baidu Inc said on Tuesday it would complete internal testing of its own ChatGPT-style project called "Ernie" in March.
Google owner Alphabet Inc announced on Monday it would launch its own chatbot service called Bard and more artificial intelligence for its search engine as well as developers.
But already, some schools and universities have responded by limiting or banning its use by students.
Some advocates predict ChatGPT will result in automating jobs away from human beings, although critics have argued that AI and robotics do not yet have the capability for that.
The tool comes from OpenAI, a for-profit research organisation co-founded by Elon Musk and investor Sam Altman, and backed by billions in funding from Microsoft .
LONDON - A new artificial intelligence model called ChatGPT is making waves as technologists promote it as a new tool that will revolutionise how people work.
How does ChatGPT work?
ChatGPT is a large language model that can generate human-like text, trained on a massive dataset of written works from the internet.
The program uses a deep learning technique called "transformer architecture" to sift through several terabytes of data that contain billions of words to create answers to prompts or questions.
ChatGPT's predecessors include GPT-3, which also generates text, but has been trained on a much larger set of data. While this makes GPT-3 more powerful, ChatGPT is faster, more capable of generating human-like answers, and is available to the public.
The bot works in the same way that AI generator tools like DALL-E 2, Midjourney, and Stable Diffusion do - but much like how those programs can create unrealistic images, ChatGPT is not always accurate.
What can ChatGPT do?
ChatGPT can write emails and essays, poetry, answer questions, or generate lines of code based on a prompt. This could be used to develop virtual assistants or quickly answer customer queries.
Content platform Jasper said about 80,000 clients have used its software to draft ads, emails, blogs and other material.
Marketing is one of the clearest businesses for today's chatbots, said Gil Elbaz, co-founder of TenOneTen Ventures, a venture capital firm.
What are the limitations of ChatGPT?
ChatGPT is trained on statistical patterns and correlations and does not have an understanding of the input or output in the same way a human would.
"Large language models have limited reliability, limited understanding, limited range, and hence need human supervision", Michael Osborne, a machine learning researcher from Oxford University, told Context.
AI tools can be prone to bias based on the data they were trained with, and a lack of transparency about that training makes it difficult to tell how the bot came to a conclusion.
The EU Agency for Fundamental Rights (FRA) has warned that algorithms based on bad data could cause harm and that safeguards should be in place to mitigating bias and discrimination.
This is exacerbated when the bot produces false information that it presents as factual, otherwise known as a hallucination.
Last year, Meta warned users that its Blenderbot 3 chatbot can make false or contradictory statements, misremember details, and "forget that they are a bot".
Will ChatGPT steal jobs?
The jobs that AI tools like ChatGPT could disrupt include repetitive or routine tasks that can be easily automated, including data entry and processing, simple customer service roles, and certain kinds of content creation.
The World Economic Forum's Future of Jobs Report estimated in 2020 that while 85 million jobs may be displaced by AI and robotics by 2025, another 97 million jobs may emerge from these changes.
However, this disruption will not be equal, with lower-wage workers, women and younger people more deeply impacted.
"ChatGPT is unlikely to put any creative professionals out of work any time soon ... the tech isn't yet fit for purpose," Gina Neff, executive director of the Minderoo Centre for Technology and Democracy, told Context.
"AI is more likely to change what we do in our jobs, rather than eliminate lots of different jobs," she said, adding that jobs will shift around new and emerging technologies without being disrupted completely.
What do creative people think of the threats posed by ChatGPT? Singer Nick Cave, responding to a song written by ChatGPT "in the style of Nick Cave", dismissed it as a "grotesque mockery of what it is to be human".
Why are AI companies being sued?
A group of visual artists last week sued AI companies Stability AI, Midjourney, and DeviantArt for copyright infringement, saying their work was used without permission to train AI tools.
Getty Images has also initiated legal proceedings against Stability AI for allegedly copying millions of its images.
A similar class action lawsuit was filed last year against Microsoft-owned GitHub for scraping code from the internet without permission, in order to train OpenAI's tools.
While copyrighted material may have been inputted to train an AI, if the result is "transformative" then firms might be within their rights under fair use copyright law, said Nick White, an intellectual property and digital specialist at law firm Charles Russell Speechlys.
The law allows people to use copyrighted material to generate new content or to comment on it, such as in YouTube videos. However, areas like code are a legal grey area, as the AI does not provide attribution.
"My gut feeling is that the outcome of these cases will grant some protection to originators of copyright works," White said.
"(But) there's a whole spectrum of infringement from production of work that is identical to work that has no similarity whatsoever, and I think it is possible we will have many more cases."
This article was updated on Feb. 7, 2023, to include the Google and Baidu announcements.
(Reporting by Adam Smith; Editing by Rina Chandran.)
| 2023-02-07T00:00:00 |
https://www.context.news/ai/what-is-chatgpt-and-will-it-steal-our-jobs
|
[
{
"date": "2023/02/07",
"position": 62,
"query": "ChatGPT employment impact"
}
] |
|
Most employees using ChatGPT, other AI tools for work ...
|
Most employees using ChatGPT, other AI tools for work aren’t telling their bosses
|
https://www.hrdive.com
|
[
"Ryan Golden",
"Senior Reporter"
] |
Amid growing public interest in artificial intelligence tools thanks to technologies like chatbot ChatGPT, more than one-third of workers in a recent ...
|
Dive Brief:
Amid growing public interest in artificial intelligence tools thanks to technologies like chatbot ChatGPT , more than one-third of workers in a recent Fishbowl survey said they had used AI tools for work-related tasks .
That represents an increase from the 27% of professionals in an early January Fishbowl survey who said they used generative AI tools for work purposes. However, 68% of respondents in the most recent survey who said they were using AI tools were doing so without first informing their bosses. The survey included responses from 11,793 Fishbowl users.
Fishbowl, a social platform for work and professional conversations, said it had observed a 107% increase in posts and comments mentioning ChatGPT between Jan. 2 and Jan. 23. The company added that users were using ChatGPT for creating resumes and cover letters, copywriting, coding and drafting sales and marketing emails.
Dive Insight:
Launched in late November 2022, ChatGPT quickly rose to global prominence as an example of AI technology. The tool, launched by OpenAI, allows any user to input prompts that generate text produced by ChatGPT’s algorithm. Users have already demonstrated numerous ChatGPT capabilities, leveraging its AI-backed tech to create anything from college essays to screenplays to songs.
As Fishbowl’s research shows, ChatGPT may have some legitimate business applications. Marketers, for example, may consider using the tech to create advertisement copy, Marketing Dive reported. OpenAI has even launched a premium version of ChatGPT that would provide enterprise users access to features such as higher message limits and faster performance, according to CIO Dive.
ChatGPT has the potential to change HR itself, but multiple sources warn that the tool is far from perfect. Stack Overflow, a program used by software developers and engineers, announced a temporary ban of ChatGPT due to inaccuracies generated by the chatbot.
Plagiarism and originality are also potential concerns. Educational institutions, for example, have banned access to ChatGPT, citing the possibility of misuse by students. Organizational pushback even led OpenAI to develop a tool, known as a text classifier, to help identify whether a piece of text was developed by AI — though this tool is still a work in progress, CIO Dive reported.
Federal regulators, including the U.S. Equal Employment Opportunity Commission, have warned about the discriminatory potential of AI, particularly in the hiring context. EEOC recently identified AI and automated systems in hiring as one of its subject matter priority areas for strategic enforcement.
| 2023-02-07T00:00:00 |
2023/02/07
|
https://www.hrdive.com/news/employees-using-chatgpt-ai-for-work-not-telling-bosses/642166/
|
[
{
"date": "2023/02/07",
"position": 91,
"query": "ChatGPT employment impact"
},
{
"date": "2023/02/07",
"position": 3,
"query": "AI workers"
}
] |
Does AI generated imagery belong in employee ...
|
Does AI generated imagery belong in employee communications?
|
https://www.benefitnews.com
|
[
"Partner",
"Creative Director",
"Paragon Design Group",
"Brunella Tipismana Urbano"
] |
The widespread use of AI-generated imagery in employee communications is around the corner, if not already here, and it offers some clear benefits.
|
The widespread use of AI-generated imagery in employee communications is around the corner, if not already here, and it offers some clear benefits. These text-to-image services allow HR teams to quickly and easily create custom images that meet their specific needs, and the increasing presence of AI-generated images in mainstream stock photo libraries suggests that they are becoming more accepted.
However, there are still some copyright concerns surrounding the use of AI-generated imagery, as the terms of use and copyright law in this area are still being developed and clarified. Despite the fact that companies are typically granted ownership of the images they create with AI, there may be other issues to consider when using these images in employee communications.
Read more: Will ChatGPT and AI lead to more layoffs?
Getting exactly the image you want
An appealing aspect of AI-generated artwork is that it can offer a level of customization and control that may not be possible with traditional stock libraries. If you're looking for an image of a collection of workers at a particular time of day and at a specific angle, it may be difficult to find an existing image that matches your needs.
With AI-generated imagery, it is possible to specify the desired elements and have an algorithm create a unique image that meets those requirements. This can be especially useful for companies that have specific branding guidelines or that want to communicate complex concepts that are unique to their industry, but are not common enough to have their own section on iStockphoto yet. Keep in mind that the quality and realism of AI-generated images can vary. So if this is a route you'd like to take, the time spent refining a stock image search will soon be replaced with the time it takes to find that perfect text prompt.
Ease of use & access
Another positive quality of AI-generated imagery is that major companies, including Adobe Stock, Canva, and Microsoft, are partnering with AI providers to offer text-to-image capabilities in their software. This will make it easier for designers to create custom images using AI, and access to these kinds of tools is likely to become as common as searching for stock photos. As Derek Murphy put it, "If AI is already on Canva, on stock photo sites, everywhere, it's going to become mainstream enough that people (paying clients) don't have a problem with it."
Read more: What ChatGPT means for the future of work
Authorship and intellectual property
The biggest source of concern when it comes to AI-generated imagery is the question of who should be credited as the creator/owner of the work. In explaining their decision to exclude AI- generated artwork, Getty Images CEO Craig Peters told the Verge , "There are real concerns with respect to the copyright of outputs from these models and unaddressed rights issues with respect to the imagery, the image metadata and those individuals contained within the imagery." Even though OpenAI's content policy allows the person who prompted the image to reprint, sell, and merchandise generative art, there is currently a legal gray area as to where the AI engine got the images it was trained on. As Atreya Mathur wrote for the Center for Art Law , "There may be infringement claims on the final image based on copyrighted artworks inputted into the AI at the time of machine learning, which may infringe the rights of copyright holders."
Read more: Why the word 'metaverse' is a hindrance to virtual work
Implicit bias
The potential for AI-generated imagery to perpetuate or amplify biases is a concern that is not unique to AI, but it is important to consider when using it in employee communications. Just as the selection of images in a stock library can reflect certain biases related to gender, ability, or race, AI algorithms can also reflect the biases of the data they are trained on, or the values of their creators. If you're going to use AI-generated imagery to communicate with employees, consider whether it may reinforce harmful biases or stereotypes. To avoid this, take care to employ the same consideration for diversity when choosing text prompts as you do with a stock image search. This ensures that the resulting artwork is inclusive and respectful .
| 2023-02-07T00:00:00 |
2023/02/07
|
https://www.benefitnews.com/opinion/does-ai-generated-imagery-belong-in-employee-communications
|
[
{
"date": "2023/02/07",
"position": 99,
"query": "AI workers"
}
] |
ChatGPT Might Not Take Your Job, but AI Will Make It More ...
|
Even if ChatGPT doesn't take your job, it could help another human replace you, says the economist who famously concluded AI could eliminate nearly half of US jobs
|
https://www.businessinsider.com
|
[
"Jacob Zinkula"
] |
Oxford economist Carl Benedikt Frey once concluded 47% of US jobs could be replaced by AI. We asked him whether ChatGPT is coming for your job.
|
This story is available exclusively to Business Insider subscribers. Become an Insider and start reading now.
In 2013, roughly a decade before ChatGPT was first released to the public, Oxford University economist Dr. Carl Benedikt Frey published some research that spooked many Americans.
In a paper he co-authored titled "The Future of Employment," Frey estimated that 47% of all US jobs were at risk of being replaced by automation as soon as the "next decade or two." The paper has been cited over 5,000 times and covered by countless media outlets, including a 2019 episode of Last Week Tonight with John Oliver.
AI hasn't replaced all of us just yet, and the paper isn't without its critics, but Frey, who's served as a consultant for the United Nations, the OECD, and several Fortune 500 companies, maintains that AI will disrupt plenty of industries in the future.
Now a decade since the paper's publication, Insider spoke with Frey about what he got right — and wrong, whether ChatGPT is coming for all of our jobs, and why even if it doesn't replace you, it might help someone else do so. It's not all bad, however. Frey says the AI takeover could be a good thing for all of us in the long run.
Artificial intelligence might not take your job, but it will have impacts
In 2013, Frey concluded that "low-skill, low-income jobs" were most at risk of being replaced by automation, and he says he still believes this to be the case.
"When autonomous vehicles arrive, they're not going to augment a taxi driver, they're going to replace those drivers," he told Insider. He also listed truck drivers, telemarketers, receptionists, cashiers, waiters, and fashion models as jobs particularly at risk of replacement.
When it comes to ChatGPT and related AI, however, Frey says job replacement is "probably not the right way of thinking about it," but workers still have some reason to fear for their job security. The reason: "more competition."
Frey points to "creative" industries like writing, music, and art, as well as graphic design, advertising, and computer programming roles, where he says widespread access to tools like ChatGPT will allow far more people to produce high quality work.
So rather than having your job "outright replaced," Frey says, ChatGPT's adoption may ultimately result in a different outcome — being replaced by another human. And even if workers manage to hang on to their jobs, he says the influx of new competition for their roles could result in lower wages.
He compares it to the introduction of ridesharing companies like Uber, which resulted in more drivers, increased competition, and ultimately led to incumbent drivers experiencing "wage cuts by around 10% or so," per his research.
Related stories Business Insider tells the innovative stories you want to know Business Insider tells the innovative stories you want to know
"Uber didn't reduce the demand for taxi drivers," he said. "It, if anything, increased the number of people driving cars for a living, but it reduced the amount the earnings capacity of incumbent drivers."
He says a similar development could play out in industries where ChatGPT is most effectively deployed.
"In my view, it's less about automation," he said. "It's more about democratization and competition, potentially leading to lower wages for people in some of these professions."
That said, Frey doesn't think AI will only replace blue-collar roles, citing fashion models and credit analysts as two jobs that could potentially be at risk.
AI has been slower to replace drivers than expected, but has also shown it has potential to do more than Frey thought
Looking back at the 2013 study, Frey acknowledges there are some things he'd have done differently if he could go back in time. That said, he believes the study's estimates regarding potential AI job replacement are still "broadly on target."
Frey points to one category of job in particular that's been automated at a much slower pace than he expected a decade ago: drivers.
"I think most people we spoke to back then said it's 10 to 15 years from now," Frey said regarding the widespread adoption of autonomous vehicles. "And 10 years later, most people are still saying that it's 10 to 15 years from now."
On the flip side, he was skeptical whether waiters and fashion models, for instance, were jobs that could potentially be automated, but says new technologies have since convinced him this is possible.
In the distant future, Frey says it's likely "everybody will be replaced" eventually by AI. As for his 47% prediction, the paper said this could happen in "perhaps a decade or two," something many people latched on to.
But Frey says he and fellow researcher Michael A. Osborne did not intend to offer a precise forecast on the "pace of automation," which he says there is not "any way to credibly forecast." Instead, he says they were focused more on forecasting the scope of jobs that could be at high risk of replacement — whenever widespread AI adoption does materialize.
AI could make the jobs of the future better
While emerging technologies have impacted many jobs in decades past, it hasn't always led to replacement.
Secretaries and bank tellers, for instance, are doing "completely different jobs" than they were a few decades ago, Frey says, but they haven't been formally replaced — their roles have simply evolved.
"I think there's this somewhat misguided distinction between replacement and jobs being changed and transformed by technology," he said.
In general, Frey says technological progress like ChatGPT is good for society. "It's the reason that we're a lot more prosperous today than a couple of hundred years ago."
And for many workers, AI tools may eventually be able to make their jobs easier.
"Some of the more boring parts of the job may disappear," he said. "We may be more focusing on generating the right ideas, asking the right questions, things that are more interesting."
At least in the near-term, Frey says humans should maintain an edge over AI in many areas. That's because there are arguably some things ChatGPT can't learn from scouring data from millions of websites.
"Humans don't just interact on the internet," he said. "We're out interacting in the real world and draw on experiences there as well. And often, we come up with things that are from a completely different domain that are unlikely to be in the training dataset."
| 2023-02-07T00:00:00 |
https://www.businessinsider.com/jobs-at-risk-replaced-ai-chatgpt-oxford-economist-2023-2
|
[
{
"date": "2023/02/07",
"position": 22,
"query": "AI wages"
}
] |
|
How will Artificial Intelligence (AI) Power New Learning in ...
|
How will Artificial Intelligence (AI) Power New Learning in Education?
|
https://education.illinois.edu
|
[] |
research in artificial intelligence—AI—in education is changing the landscape for teachers and students. Here, Lane and Tissenbaum share their AI research and ...
|
by Tom Hanlon / Feb 7, 2023
H. Chad Lane and Mike Tissenbaum are two of a handful of College of Education professors whose research in artificial intelligence—AI—in education is changing the landscape for teachers and students. Here, Lane and Tissenbaum share their AI research and views regarding its use in education.
A chatbot could have written this article. (But it didn’t. Honest.)
It could also write a college student’s essay. And, based on the assessment of students’ writing skills lately, it could probably write a better essay than at least some students could.
That’s just part of the ever-evolving world of technology. As with any advance, the increasing use of—some would say infiltration of—artificial intelligence in our lives brings a mix of reactions: intrigue, excitement, skepticism, fear.
The Explosion of AI
H. Chad Lane likens the explosion of AI to that of televisions. In the 1930s, TVs were affordable only to the privileged few: a set cost anywhere from $200 to $600; the average annual salary was $1,368. But from 1950 to 1960, the percentage of US households that owned a television rose from 9% to 87%.
“People were worried that no one was going to leave their home anymore, that they were going to watch TV all day long,” says Lane, associate chair and associate professor in the College of Education’s Educational Psychology department. “But that didn’t bear out.”
In the same way, Lane says, people are now concerned about the advances of AI and how it will impact our lives, in education and beyond. And he wants to allay their fears.
“AI does have some risks to it,” he admits. “There’s always an issue about privacy. AI systems need data to do things that respond to them. It’s a benefit/cost question we have to ask. There’s always the risk that someone with access misuses your data because it’s sitting on a server somewhere. But in a lot of cases, we have some pretty robust mechanisms for privacy and safety. For example, de-identifying data, using IDs rather than names.”
Lane also acknowledges the skeptical view many have of AI.
“I get that it’s kind of creepy that we’re trying to make computers more like people, but I’m not convinced that AI is specifically unique from previous technological advances,” he says. “It’s been the tropes of ‘evil AI’ in movies like The Terminator, and that image still lingers, but it’s getting better with the positive examples of AI out there."
Empowering Teachers
Mike Tissenbaum points out some of those positive examples that are specific to education.
“AI is really good at taking a lot of complex, real-time data and processing it and using the kinds of patterns that often would take weeks and weeks and weeks to do qualitatively or quantitively,” says Tissenbaum, assistant professor in Curriculum & Instruction.
It can also be used to make suggestions for grouping students for optimal collaborations and discussions based on their understanding of the content. And it can provide students the materials or prompts to scaffold discussions.
“AI is not replacing the teacher,” Tissenbaum emphasizes. “It takes care of the grinding, hard-to-do work so the teacher can focus on the students. It can really empower the teacher and the students.”
Lane agrees. “I can say with 100 percent certainty that no one in the AIED community has that goal [of replacing teachers], because most of us are or were teachers. We understand what it takes to teach and we understand how unique and special that is. Teachers are irreplaceable. So, we’re building tools that can make their lives better.”
In Lane’s research, those tools are primarily aimed at helping middle school and high school students in STEM classes, even though AI can and does apply to all levels of education—and beyond, such as tutoring systems for aging adults.
“It’s generally most helpful for beginners,” Lane says. “The greatest potential is in helping kids who are struggling at the beginning of learning math and science, because that’s where they have the most misconceptions and the greatest gaps in knowledge—and often, reduced motivation. So, you have to think about making it engaging and interesting and fun and adapting it to their interests.”
"Not a Panacea"
Tissenbaum is optimistic about the use of AI in education, but cautions that it’s not a panacea.
“We have to be cautious about the willy-nilly implementation of these things and understand the risks so that we can innovate responsibly,” he says. “I’ve been using AI tools since 2010 at some level. I believe AI is going to be quite transformational in time, but none of this is ‘We’ve just solved education now.’”
Tissenbaum believes the more commonplace use of AI in classrooms across the country is at least 10 years out. “We have a lot of people doing interesting work in AI, both here and elsewhere, but we’re just now starting to understand it in small implementation,” he says. “I’d be cautious to rush to scale yet until we really know what it does for learning. But I am very positive about the directions that we’re heading because I do believe people are thinking about this in the right ways.”
AI Supports Collaborative Learning
Tissenbaum is part of a multi-university team working on a large NSF National AI Institute for Student-AI Teaming project that focuses on how AI can support students and teachers as they engage in collaborative learning.
“We’re building models and using complex data mining to understand speech patterns in ways that would be very hard for us to know on our own,” he says. “And we’re developing agents that interact with the students and let the teacher know how to engage the kids and get them back on track. All of this is based on a lot of qualitative data analysis that would be very hard for a teacher to do all over her classroom at once. We’re using machine learning and AI to process this data and become an integral part of the classroom.”
Tissenbaum is also working on another NSF grant, called SimSnap, developing and researching collaborative learning in middle school life science classes using tablet-style computers that support simulations of biological systems.
“We’re looking at students combining the written word and spoken word together, doing data mining, and trying to find associations for the kids,” he says. “So, we do a lot of natural language processing in real time, using speech-to-text tools and mining that to understand what the kids are talking about.”
The Use of AI in STEM Classes
Lane’s work in computer science and natural language processing began back in the late 1990s when, as a graduate student, he built a natural dialogue system to help his students, who were learning to write programs, with natural language processing. Since coming to the University of Illinois in 2015, he’s worked on several grants that are studying Minecraft for understanding science, astronomy, and engineering. Minecraft is a 3D game that offers players a great deal of freedom (there are no preset goals) and creativity to interact with.
“My students and I are looking at how AI techniques can be used to assess learner knowledge and behaviors in educational games and build agents that help them in a variety of ways,” Lane says. “Much of my research focuses on using Minecraft as a STEM learning environment, so we have built models that analyze learners' exploratory behaviors, how they make scientific observations, and how they approach investigating planets for habitability. Kids get to explore simulated exoplanets in Minecraft, take measurements of relevant variables such as oxygen and radiation, etc., and then build habitats for survival.”
His work, as does Tissenbaum’s, involves creating agents that interact with students. In fact, he is researching how the visual presentation of the agent influences a learner’s behavior. “We’re looking at gender, race, how they’re dressed,” Lane says. “And how they help a learner. Are they more hands off and just available or do they sometimes give demos? We’re implementing a variety of strategies for these agents to support learners in Minecraft.”
To point out the necessity for an effective agent, he dredges up the well-intentioned but poorly-executed Microsoft Word agent, Clippy, who appeared in the form of a paper clip and asked obvious (and irritating) questions as you worked on a document.
“Clippy is often referred to as the wrong way to do an agent,” Lane laughs. “We work carefully to make sure our agents are more helpful, fun, interesting, and engage the kids in meaningful ways. We want the kids to come out of it with a better understanding and a better attitude about all of the topics that they’re learning about, and that the agents have influenced that learning in some way.”
The Evolution of AI
AI in education is hardly new. The International Artificial Intelligence in Education Society has been around since 1997, boasting 1,000 members from over 40 countries. Lane edited a special 25th anniversary issue of the society’s journal, the International Journal of AI in Education; he served on the society’s executive committee for six years and was twice nominated to be president. The journal he edited focused on the next 25 years of AI in education research.
“One thing that’s come out of all these decades of research is the field is no longer taking this AI hammer and trying to solve every problem with it,” he says. “In the early days, it was ‘I’m going to take this AI thing and build an educational tool out of it.’ But that’s no longer true.”
Instead, he says, the research is now focused on where AI can make a real difference in education.
“We’re trying to make strides on how AI systems can assess learners in more nuanced and culturally relevant ways, giving kids immediate feedback and helpful suggestions on their homework, and reporting to the teachers on how well the kids understood it,” he says. “AI has actually advanced the science of learning. We’ve learned more about how human beings learn because we have these AI tools.”
"Don't Do Tech for Tech's Sake"
Tissenbaum sees a distinction between AI researchers who are not so focused on the educational learning side of the field and those for whom the sole focus is on enhancing the educational experience of students. He gives the example of speaker diarisation, which is the process of partitioning audio streams of speech into homogenous segments according to the identity of each speaker. The process allows researchers to know who spoke when and to group segments together.
“They’re like, ‘Wow, we went from 45 percent to 65 percent accuracy,’ he says. “From a tech standpoint, that’s good. But from a supporting students standpoint, that’s not accurate enough. We need to be mindful about getting things out there and trying it but understanding the potential impact. If you can fail or harm students, why are you doing this? Don’t just do tech for tech’s sake.”
Instead, he says, research needs to focus on enhancing education. “It can’t just be, ‘Can we use the tools?’ It’s ‘What can we do to advance learning?’ That’s what I try to do in my work.”
A Variance in Programs
The proliferation of AI tools, and specifically AI tools in education, means, of course, that there is a wide range of tools to choose from and that some tools are more effective than others in enhancing the learning experience.
“Imagine two computer systems helping a student, and one system just tells the student if they were right or wrong, while the other looks at the steps the student took, the things they typed in, their ideas, and it processes that mapped up against a cognitive model of how to think about it,” Lane says. “You can give so much deeper, richer, contextually relevant feedback to the child in the latter situation. And that’s why AI has an advantage over the more traditional systems. This advantage has been empirically validated in studies over and over again.”
The system that provides that nuanced and detailed feedback is a knowledge-based system. Lane says such systems are better in almost every case.
“The problem is, they’re hard to build,” he notes. “They take a lot more time and effort. Some companies have partially solved that problem, but that’s why we don’t see AI systems in every school. But there are plenty of people looking at that and trying to scale it up.”
Bots are Far From Perfect
Building knowledge-based systems is one problem. Another is, as Tissenbaum notes, “AI is designed by white males in Silicon Valley for use by white males in Silicon Valley, and it uses data that is of interest to white males in Silicon Valley.” The result is both limiting and biased.
For example, he brings up one of the latest marvels in AI, ChatGPT, which was released at the end of November. The chatbot employs both supervised and reinforcement learning techniques as it interacts with users, applying a deep learning technique called “transformer architecture” to sift through several terabytes of data that contain billions of words to create answers to prompts or questions.
ChatGPT can do a lot: It can write articles (again, not this one!), letters, and, yes, college students’ essays. Google reports that it would hire the bot as an entry-level coder if it interviewed for the job.
Then again, ChatGPT and other AI bots regularly show their “human side” by making errors. For example, CNET, the tech news and product reviews publication, has used AI to write articles. It had to correct multiple errors in one article that explained compound interest. One answer had a person earning $10,300 in interest, instead of the correct $300.
“ChatGPT is wrong—a lot,” Tissenbaum says. “It’s mostly a marketing gimmick [for its developer, OpenAI] to show it can write an essay, it can do this or that. But you don’t want it to teach a critical pedagogy to students because it’s probably not going to be historically accurate.” The content could be skewed by racism, biases, and otherwise factually incorrect information. Tissenbaum himself tested ChatGPT, having it write an essay for him.
“It was kind of right,” he says. “Maybe 80 percent. Is that good enough? It could probably replace an undergrad essay that’s probably only 80 percent right.”
The possibility of using ChatGPT to write an essay is obviously problematic for instructors. “Maybe we’re going to have to change how we operate in undergrad courses,” Tissenbaum says. “Who knows? The essay might become antiquated. I’ve heard people talk about having ChatGPT create the essay and having students critique it.”
"Teach Healthy Skepticism"
Lane, on the other hand, sees the good side of ChatGPT.
“My early assessment is that ChatGPT is a good thing,” he says. “Human-centered AI, the area of AI focused on how to create AI systems that interact with and collaborate with humans, is what we all want. The potential to support creative processes such as writer’s block, explore new solutions, design and plan events or software or anything, and learn, seems endless to me.”
The bigger issue, Lane says, is teaching students how to think about and use AI.
“It’s critical to teach kids that AI systems are driven by human data,” he says. “Anything ChatGPT tells you is derived from a knowledge base from human content. So, it could be wrong. As long as kids realize what it tells them is not 100 percent accurate, it’s not an oracle, that’s good. Teach healthy skepticism. That’s a good thing in general.”
A Positive Future
The bottom line, Lane says, is that AI can be used to help students in “amazingly powerful ways.”
Human-centered AI—systems that amplify and augment rather than displace human abilities—are here to stay. And Lane sees that as having profoundly positive implications, “if we make the investment in it and choose our research agenda wisely.”
“The idea of human-centered AI has really caught on,” he says. “AI has been successfully applied to education in many settings, and I think it is something that will continue to explode. AI can achieve a deeper awareness of how we think and solve and work as individuals. This awareness will continue to deepen, especially with respect to age, individual needs, and culture. AI systems will continue to evolve to interact with us in more meaningful ways, to help us solve problems, be creative, and learn. I think this all points to a very positive future.”
| 2023-02-08T00:00:00 |
2023/02/08
|
https://education.illinois.edu/about/news-events/news/article/2023/02/08/the-power-of-ai-in-education
|
[
{
"date": "2023/02/07",
"position": 7,
"query": "AI education"
},
{
"date": "2023/02/07",
"position": 2,
"query": "artificial intelligence education"
}
] |
American Image Press - Representing Journalism
|
Representing Journalism
|
https://www.ifpo.net
|
[] |
Photojournalism is an important form of journalism that tells the stories of ... Freelance Photographers Association: Top 10 Reasons to Join IFPO ...
|
Photojournalism is an important form of journalism that tells the stories of people, events, and cultures both near and far. As a freelance photographer, you have the unique opportunity to be the one who captures these moments and helps bring them to life for others. However, with this great responsibility comes the need to be part of a professional organization like the International Freelance Photography Organization. IFPO represents photojournalists from all over the world and provides several resources and benefits that can help you in your career. In this article, we’ll explore some of the reasons why it’s important to be a member of IFPO as a freelance photographer.
Who We Are
The International Freelance Photography Organization stands for ethical excellence, captivating creativity, and worldwide representation of professional photographers. As a collective of forward-thinking photojournalists, we work to elevate the reach and impact of visual storytelling from all corners of the world. At IFPO, our members actively promote the importance of photojournalism in advancing knowledge, culture, and, understanding in both local and global arenas. We believe that photography has the power to bring about meaningful statements and conversations, helping to preserve iconic moments in time. We are dedicated to growing sustainable collaboration with other affiliations as well as providing opportunities for our members around the globe.
What We Do
As the international organization representing photojournalism and its use of freelance photography, IFPO provides a platform for photographers to connect, share their work, receive assistance, and support, and learn about opportunities in the field. We bring together talented photographers from across the world on our network, which allows them to benefit from knowledge exchange as well as offer mutual support through constructive criticism. IFPO also gives those just starting out in photojournalism a place where they can seek advice from industry experts, find useful resources, and understand the requirements for entry. Through enabling collaboration with peers and offering valuable insights into the world of photojournalism, International Freelance Photographer Organization is committed to connecting professionals with exceptional opportunities that further fuel their creativity.
Why IFPO Supports Photojournalists
Photojournalism is a powerful tool for speaking truth to power and raising awareness of the issues that face us as a global society. It is essential to ensure the stories being told are accurate and diverse, and that those behind the lens have their voices heard. That’s why International Freelance Photography Organization believes it’s important to support freelance photographers around the world. Through their unique perspectives, these photographers can help create a more representative body of work that accurately reflects the reality of our modern world. We believe that by amplifying these stories, we can help shape an enlightened future for us all.
Benefits International Freelance Photographers Organization Offers
Support while on assignment: With more than 90,000 active members and official recognition in 143 countries, IFPO is a formidable organization. Its membership gives you the affiliation, support, and credentials you need to bring you and your camera where you want to go. The powerful IFPO organization holds the weight to pave the way for individual photographers to achieve by supporting one other and sharing true-life success stories.
With more than 90,000 active members and official recognition in 143 countries, IFPO is a formidable organization. Its membership gives you the affiliation, support, and credentials you need to bring you and your camera where you want to go. The powerful IFPO organization holds the weight to pave the way for individual photographers to achieve by supporting one other and sharing true-life success stories. Proven programs: To help you gain access with your camera, get published, and grow your portfolio.
To help you gain access with your camera, get published, and grow your portfolio. Ability to make money: Many members join in IFPO money-making initiatives to “jump start” a secondary income from photography without altering their current careers. Others who are currently making money in photography use IFPO programs to make their photography income increase even faster.
Many members join in IFPO money-making initiatives to “jump start” a secondary income from photography without altering their current careers. Others who are currently making money in photography use IFPO programs to make their photography income increase even faster. Worldwide exposure: International divisions and affiliates of IFPO have been created to better serve big groups of photographers who are concentrated in certain areas around the world. Divisions are operating in Chile, Thailand, India, Denmark, Japan, and Puerto Rico.
How You Can Join
If photography is a passion, then joining the International Freelance Photography Organization can help you to develop that passion further. Since 1984, IFPO has provided its members with a wealth of resources and learning opportunities, from in-depth articles about photography and photojournalism to programs to help you succeed in your career. Not only does membership give you access to all these great learning materials, but it can also help to connect you with other professionals in the industry. Furthermore, joining IFPO will give you more exposure to your work, as the organization provides a platform for showcasing freelance photojournalists’ work and experiences. Interested in joining IFO? Visit our website today to become a member – don’t miss this opportunity!
| 2023-02-07T00:00:00 |
https://www.ifpo.net/representing-journalism/
|
[
{
"date": "2023/02/07",
"position": 78,
"query": "AI journalism"
}
] |
|
Are You Prepared to Be Interviewed by an AI?
|
Are You Prepared to Be Interviewed by an AI?
|
https://hbr.org
|
[
"Zahira Jaser",
"Dimitra Petrakaki",
"Phd",
"Is Aassociate Professor At The University Of Sussex Business School",
"The Director Of The Sussex Mba",
"Associate Fellow Of",
"Is Professor Of Technology",
"Organization At The University Of Sussex Business School",
"Co-Investigator Of The Esrc-Funded Digital Futures At Work Research Centre. Her Work Focuses On The Implications Of The Introduction Of Digital Technology For The Organization Of Work. She Is The Associated Editor Of The"
] |
AI-led interviews use the data collected to automatically generate a prediction on whether the candidate is the person they are looking for. For example, AI ...
|
During the isolation of the pandemic, many human resource management processes moved online. And even as life goes back to being more in person, many of these processes are here to stay. One is virtual, or pre-recorded job interviews, which are increasingly guided by artificial intelligence (AI). These interviews typically shorten the hiring process, making it cheaper for companies to find the right candidates.
| 2023-02-07T00:00:00 |
2023/02/07
|
https://hbr.org/2023/02/are-you-prepared-to-be-interviewed-by-an-ai
|
[
{
"date": "2023/02/07",
"position": 19,
"query": "artificial intelligence hiring"
}
] |
There's hope AI companies could revive downtown S.F. ...
|
There’s hope AI companies could revive downtown S.F., but economists aren’t so sure
|
https://www.sfchronicle.com
|
[
"Chase Difeliciantonio"
] |
The San Francisco metropolitan statistical area steadily is losing its share of artificial intelligence job postings, data shows.
|
The San Francisco metropolitan statistical area steadily is losing its share of artificial intelligence job postings, data shows. Carlos Avila Gonzalez, Staff Photographer / The Chronicle
The buzz in recent weeks over leaps in artificial intelligence, or AI, technology has caused venture capitalists and marquee companies like Microsoft to pour billions of dollars into the trending industry. And with many of the most recognizable AI companies based in San Francisco, there are hopes that the rising industry could shift the city’s fortunes and not just revitalize its tech sector, but help fill empty downtown streets, offices and shops with the next wave of tech workers whose spending could filter through the rest of the city’s economy.
But some economists aren’t so sure.
On one hand, overall hiring in San Francisco’s tech sector in recent months has been flat. That is a mostly positive sign, according to city data and San Francisco Chief Economist Ted Egan, especially since ongoing layoffs have battered companies based in the city in recent weeks and months.
Advertisement Article continues below this ad
But job posting data aggregated from thousands of hiring sites nationally by jobs site ZipRecruiter shows the San Francisco metropolitan statistical area steadily losing its share of job postings in the burgeoning AI field. It’s not entirely clear where those jobs might be located from the data. Some postings could be located in other cities, or a remote role might not have a location tied to it at all.
ZipRecruiter’s analysis shows that the San Francisco area’s average share of active U.S. AI online job postings peaked during the past three years at 7.35% in May 2020. The most recent numbers show that number at just under 3% in January, having mostly dropped month to month since the high point.
Embed 5022278Z-1675466948160 San Francisco's share of U.S. AI job postings on ZipRecruiter, 2020-23
That’s a worrying sign for the city and the region, said ZipRecruiter Chief Economist Julia Pollak.
Advertisement Article continues below this ad
“San Francisco has kind of gotten the rawest deal of all,” Pollak said. Whereas the city once had the heaviest concentration of tech jobs nationally, “geography has become so much less important than before the pandemic.” The huge shift to full or partial remote work has allowed companies, even if they are based here, to hire people anywhere, she added.
“It doesn’t seem likely that San Francisco is going to manage to claw back those jobs,” she said.
A city analysis from April last year showed that 33% of local office workers would probably do their jobs remotely, up from an estimate of 15% in January 2022.
And that could have profound effects for the city, which has continued to lose residents, and the ongoing recovery of its economy.
“Once you have a critical mass of tech workers leaving San Francisco and a critical mass of people hired elsewhere, you can’t go back,” Pollak said. “With people leaving the area, there are more properties and offices vacant,” which has led to less foot traffic and economic activity in places like downtown, she said.
Advertisement Article continues below this ad
San Francisco saw a nearly 46% office occupancy rate during the last full week of January according to office card-swipe company Kastle Systems, slowly creeping up from where it has hovered, around 40%, for months.
San Francisco city data shows that remote work has led to continually rising office vacancies, however, which were above 25% in the fourth quarter of last year.
But Egan, the city’s chief economist, was quick to differentiate job postings from actual hires.
“Attempts to hire are not necessarily net new growth,” he said, referring to the postings aggregated by ZipRecruiter, which looked for keywords in job listings to pick out AI and machine-learning roles.
He noted that companies in San Francisco and elsewhere may also be adding AI keywords to their job postings to make them appear more attractive, because the industry is seeing so much interest right now.
Advertisement Article continues below this ad
“The important context is that job listings can be a leading indicator for the labor market,” Egan said. “Like all leading indicators, they come with an element of inaccuracy.”
The city, in its monthly economic analysis, does not differentiate AI jobs from tech more broadly, Egan said.
That is despite seemingly daily stories of tech companies large and small cutting hundreds or thousands of jobs.
San Francisco’s most recent monthly report shows that the unemployment rate dropped to 2% in January. The report noted that while the information sector, which includes many tech roles, lost jobs on a net basis, growth in professional and technical services, which also includes some tech as well as health care and retail trade, more than made up for the loss.
“The real question is, given all the layoffs, why isn’t tech employment dropping faster?” Egan said.
Advertisement Article continues below this ad
Some reasons could be that not all layoffs at companies based in the city affect workers based there. There are also frequently lag times between layoff announcements and actual separations, Egan said. It’s also likely that people are being laid off but finding other jobs.
Federal government statistics released last week showed that jobs in professional and business services jumped nationally last month by 82,000, half of that number in the professional, scientific and technical services.
Egan said it was difficult to say, if indeed the city’s share of AI jobs was trending down, why that might be, but he cast doubt on San Francisco-based companies offering enough remote positions to meaningfully drive down the number of jobs in that industry in the San Francisco area.
Whatever the data says, some AI industry luminaries remain bullish on the city, despite its shortcomings.
In a recent tweet, Sam Altman, CEO of OpenAI, whose ChatGPT product has impressed users with its fluent responses if not its accuracy, called San Francisco the “center of the AI revolution.”
“S.F. remains super relevant for the next decade,” Altman said.
| 2023-02-06T00:00:00 |
2023/02/06
|
https://www.sfchronicle.com/sf/article/ai-jobs-artificial-intelligence-17764412.php
|
[
{
"date": "2023/02/07",
"position": 22,
"query": "artificial intelligence layoffs"
}
] |
A New AI Tool to Fight a New AI Tool
|
A New AI Tool to Fight a New AI Tool
|
https://www.kornferry.com
|
[
"For More Expert Insights"
] |
artificial intelligence. Three months ago ... But it could be problematic for evaluating performance, screening job candidates, or conducting layoffs ...
|
How’s this for meta: artificial-intelligence tools are being tested to protect against copyright infringement, plagiarism, and other liabilities that could potentially arise from using... artificial intelligence.
Three months ago, ChatGPT debuted—the first artificial-intelligence bot to produce original content virtually indistinguishable from that of a human brain. Now, the creators of that software are beta testing a new tool that can (or so they say) determine whether a text was written by a person or a machine.
The applications could be many, from identifying disinformation campaigns to detecting when a job candidate is has used AI for a cover letter. But experts worry the software will only create more challenges for leaders already caught in an AI rabbit hole. “The mushing of original thinking and discernment and artificial intelligence is dangerous for employees, managers, and leaders,” says Andrés Tapia, a senior client partner and global diversity, equity, and inclusion strategist at Korn Ferry.
Since ChatGPT and other “generative AI” bots draft responses based on user questions and prompts, the more the software is used, the more human it sounds. That could be beneficial in automating emails, onboarding new employees, or answering basic customer-service questions. But it could be problematic for evaluating performance, screening job candidates, or conducting layoffs, says Tamara Rodman, a senior client partner in the Culture, Change, and Communications practice at Korn Ferry. One job applicant could, for example, pass an initial screening using work produced mainly by a bot, while another, who really did write their own cover letter, could be ruled out for sounding too much like a bot.
But how well the software will work is an open question. OpenAI, creator of both the ChatGPT and AI-text detector software, says that the new tool has so far correctly identified only 26% of AI-written content, while mistaking human-written text for AI 9% of the time.
The numbers could improve, but Chris Cantarella, a senior client partner and global sector leader for software at Korn Ferry, worries that firms may end up placing the judgments of AI on par with, if not above, that of humans. “How long before society broadly agrees AI should be in the superior position overall to make the ultimate judgments?” asks Cantarella, adding that it’s a question with important talent and workforce ramifications.
There’s also a concern that firms and schools trying to root out cheating might inadvertently stifle innovation for businesses. After all, the attempt to ban or limit ChatGPT isn’t without precedent—Google and Wikipedia met similar resistance at some schools. Some experts fear the increases in productivity and efficiency that AI promises could be quashed before they can be realized. “There are places where using ChatGPT will matter and places where it won’t,” says Juan Pablo Gonzalez, a senior client partner and sector leader for the Professional Services practice at Korn Ferry. “Leaders are going to have to evolve how they think about writing.”
For more information, contact Korn Ferry's Software and Platforms practice.
| 2023-02-07T00:00:00 |
https://www.kornferry.com/insights/this-week-in-leadership/a-new-ai-tool-to-fight-a-new-ai-tool
|
[
{
"date": "2023/02/07",
"position": 97,
"query": "artificial intelligence layoffs"
}
] |
|
Design Program | SoE Undergrad Handbook
|
Design Program
|
https://ughb.stanford.edu
|
[] |
Any CS247 class (ex: CS 247A: Design for Artificial Intelligence) (3-4 units) ... Choose DESIGN 170: Visual Frontiers, or one 3-5-unit course from the ...
|
The mission of the Design (formerly Product Design) program is to graduate designers who can synthesize technology, aesthetics, and business factors in service of human need. Students emerge with both a strong engineering depth and technical know-how, as well as creative, visual thinking abilities and a deeply human-centered orientation to problem-solving. Their ability to seamlessly integrate across these two “right brain / left-brain" ways of thinking empowers them to make and build products, services, and experiences with transformative potential in service of people and planet.
With the transition from Product Design to Design, the degree continues to provide a strong technical engineering foundation, while expanding both the ways of making and domain application areas for design.
You’ll find everything you need to know about the undergrad Design degree on this page. Please also visit our undergraduate Design program site to learn more about the program vision, explore the Domain areas, and discover more resources and support. If you’re looking for more information on the graduate Design program, please go here.
Completion of the undergraduate program in Design leads to the conferral of the Bachelor of Science in Design (DESIGN-BS). Going forward, all freshman or sophomores declaring design will receive the new Design degree. Product Design has been retired.
The Design major has three possible Methods tracks:
Physical Design + Manufacturing
AI + Digital User Experience
Human Behavior + Multi-stakeholder Research
In addition to the Methods tracks listed above, students will also choose from one of four Domain Focus spheres:
Designing for the Planet
Designing for Health
Designing for Social Impact
Designing for Biological Futures
See Requirements below for detail on each Method and Domain, and specific course options and requirements. Important Note: There are three versions of Program Sheets to reflect the three Method Depths offered. Some of the Math, Science, and SoE Fundamentals vary depending on Method Depth. Use the information below as a general guide, but please refer to the individual program sheets for the most precise look at requirements.
Program Sheets , a Core Flowchart, and 4-Year Plans are available now
Find current major requirements for this and all other School of Engineering major programs at Explore Degrees
For advising questions, please email us at [email protected]. We’ll be checking messages and responding on a weekly cadence.
Student Services: Bldg 550, Room 169, Colton Brasel, [email protected]
For instructions on how to declare the Design major, see bottom of page.
2023-24 Requirements
Math, Behavioral Science, and SoE Science must reach a combined total of 30 units minimum. See Note 1 below for using AP or IB credit to satisfy major requirements.
Mathematics
15-20 units minimum (requirements vary slightly by Method Depth; see Note 1)
STATS 60/160 (recommended) or STATS 110
MATH 19, 20, 21 Calculus
MATH 51 or CME 100 (required for Physical and Digital Methods Depths only)
Behavioral Sciences
Choose 1-2 courses of 3-5 units each from the following list (no more than 2 courses apply to 30-unit minimum):
BIO 150 / HUMBIO 160: Human Behavioral Biology
MS&E 180: Organizations: Theory and Management
MS&E 184: Future of Work: Issues in Organizational Learning and Design
PSYCH 1: Introduction to Psychology
PSYCH 30: Introduction to Perception
Psychology course numbered 31-180 listed for at least 3 units
Note that PSYC (Psychiatry) courses are not acceptable substitutes.
Additional SoE Math and Science
Additional approved courses from SoE-approved lists to reach the required 30 unit minimum (No additional social or behavioral science courses are allowed)(see Note 1).
PHYSICS 41 is required for the Physical Design + Manufacturing track
CS 103 and/or CS 109 recommended for the Digital Methods track
Technology in Society
Choose one course from list of SoE-approved courses on Approved Courses; the course must be on the list the year it is taken.
Engineering Fundamentals (2 courses required)
CS 106A Programming Methodologies required for the Digital track
ENGR 14 Intro to Solid Mechanics required for the Physical Design+Manufacturing track
Check Methods and Domains in Design Depth for suggestions within each track and domain
Design Core (all required)
Course* Title Units Quarter DESIGN 1 Introduction to Design (See Note 2) 4 A,S DESIGN 11 Visual Thinking (same as ME 101) 4 A,W,S DESIGN 101 History and Ethics of Design (same as ME 120) 3 W DESIGN 121 Introduction to Human Values in Design (same as ME 115A) 4 A/S DESIGN 131 Advanced Product Design: Needfinding (same as ME 216A) 4 A DESIGN 141 Product Design Methods (same as ME 115B) 4 W DESIGN 151 Business Design: Impact and Implications (same as ME 115C) 3 S DESIGN 160R Design Formation (see Note 4) 1 A,W DESIGN 170 Visual Frontiers (same as ME 125) or other visual expression elective (see Note 3) 3 W,S
Methods Depth
Students will get to sharpen making skills and abilities and gain professional fluency by choosing one of following three Method Depths tracks.
(A) Physical Design + Manufacturing
Methods range from classes on materials and mechanisms to understand what is possible with physical design, to manufacturing processes and supply chain logistics to understand how physical design is implemented.
One of the following foundational classes in making with physical materials:
ME 80: Mechanics of Materials (3 units)
CEE 101a: Mechanics of Materials (4 units)
Both applied classes in aspects of physical manufacturing:
ME 102: Foundations of Product Realization (3 units)
ME 103: Product Realization: Design and Making (4 units)
(B) AI + Digital User Experience
Methods range from foundational classes on programing methodologies and human computer interaction to applied courses on digital prototyping, user experience design, and incorporating AI and data science.
The following foundational class in programming:
CS 106B: Programming Abstractions (5 units)
One of the following applied classes in artificial intelligence:
CS 129: Applied Machine Learning (3-4 units)
CS 131: Computer Vision Foundations and Applications (3-4 units)
CS 124: From Languages to Information (3-4 units)
CS 223A: Intro to Robotics (3 units)
One of the following applied classes in human augmentation or interaction:
Any CS247 class (ex: CS 247A: Design for Artificial Intelligence) (3-4 units)
SYMSYS 245: Cognition in Interaction Design (3 units)
CS 448B: Data Visualization (4 units)
CS 278: Social Computing (3-4 units)
CS 347: Human-Computer Interaction: Foundations and Frontiers (3-4 units)
CS 377Q: Designing for Accessibility (3-4 units)
Optional but suggested additional applied course in AI + Digital Experience:
COMM 172: Media Psychology (5 units)
PSYCH 30: Introduction to Perception (4 units)
BIOMEDIN 220: Artificial Intelligence in Healthcare (BIODS 220, CS 271) (3-4 units)
CS 372: Artificial Intelligence for Disease Diagnosis and Information Recommendations (3 units)
PSYCH 293: What makes a good explanation? Psychological and philosophical perspectives
(C) Human Behavior + Multi-stakeholder Research
This method depth is an opportunity for students to develop an understanding of how to build the body of knowledge that will allow them to execute effective design AND how to use research to modify and evolve design directions as they manifest in the world.
One of the following foundational classes in social theory:
COMM 1: Introduction to communication (5 units)
MS&E 180: Org Behavior (4 units)
MS&E 184: Future of Work (4 units)
ANTHRO 1: Introduction to Cultural and Social Anthropology (3-5 units)
SOC 1: Introduction to Sociology (5 units)
SOC 180A: Foundations of Social Research (4 units)
PSYCH 70: Social Psych (4 units)
PSYCH 75: Cultural Psych (5 units)
PSYCH 80: Personality and Affective Psych (3 units)
One of the following qualitative methods courses:
HUMBIO 82A: Qualitative Research Methodology (3 units)
EDUC 450C: Qualitative Interviewing (ENVRES 231) (3 units)
ANTHRO 91: Method and Evidence in Anthropology (5 units)
One of the following quantitative methods courses:
ANTHRO 116: Data Analysis for Quantitative Research (5 units)
COMM 106: Communication Research Methods (5 units)
MS&E 125: Introduction to Applied Statistics (4 units)
PSYCH 290: Natural Language Processing & Text-Based Machine Learning in the SocSci (4 units)
STATS 191: Introduction to Applied Statistics (3 units)
Optional but suggested additional applied course in applied research:
CS 377U: Understanding Users (3-4 units)
CS 347: Human-Computer Interaction: Foundations and Frontiers (3-4 units)
CS 278: Social Computing (3-4 units)
COMM 124/224: Truth, Trust, and Tech (5 units)
MS&E 92: Introduction to Health Policy Modeling
Domain Focus Area
Along with building a depth in selected methods of design, students will also get to take courses in chosen domain focus area, and have the opportunity to apply these frameworks for problem solving in another field. This is a chance for students to explore an area of interest to them, and to apply their design abilities in context. Taking courses in a domain area encourages a design practice that values curiosity, deep immersion, and x-disciplinary collaboration.
Students are encouraged to use their domain coursework to prepare them for their senior capstone project if they choose, but domain coursework does not prescribe capstone direction.The focus areas described below include class options for students to take three courses: one foundational, one applied, and one that examines future horizons.
Explore all of our domain course offerings within each of the spheres on our Domain Course Appendix. You’ll also find sample 3-course pathways that correspond to focused application areas on our domain landscape maps. We invite and encourage you to submit a Domain Petition form to propose classes that may fit in our domain spheres, but are not already on the list.
Designing for the Planet : a domain sphere including Climate, Environment, Oceans, and Energy (and more)
Gain knowledge around environmental problem solving at macro and micro scales, on all corners of our planet.
: a domain sphere including Climate, Environment, Oceans, and Energy (and more) Gain knowledge around environmental problem solving at macro and micro scales, on all corners of our planet. Designing for Health: a domain sphere including Healthcare & Health Technology Innovation (and more)
Gain understanding in anatomy, physiology, healthcare systems, and health technology while exploring a new era of personalized, accessible, and patient-centered care.
a domain sphere including Healthcare & Health Technology Innovation (and more) Gain understanding in anatomy, physiology, healthcare systems, and health technology while exploring a new era of personalized, accessible, and patient-centered care. Designing for Social Impact : a domain sphere including Global Development, Social Systems, Social Inequity (and more)
Investigate domestic and global governance and their intersection with development, economics, and a more equitable society.
: a domain sphere including Global Development, Social Systems, Social Inequity (and more) Investigate domestic and global governance and their intersection with development, economics, and a more equitable society. Designing for Biological Futures: a domain sphere including Living Matter and Synthetic Biology (and more)
Learn about biofutures and explore the possibilities of building with biology.
Capstone
For their Capstone, students will scope and execute design work that integrates and draws upon what they’ve learned across their methods depth and potentially their domain focus area, as well.
DESIGN 161A: Advanced Design: Capstone 1 (req'd; see Note 5) (same as ME 216B)
DESIGN 161B: Advanced Design: Capstone 2 (req'd; see Note 5) (same as ME 216C)
Notes:
Math and Science: The School of Engineering list of approved math and science courses can be found on the Approved Courses page of the UGHB website. Take all three of MATH 19/20/21 or may use 10 units AP BC and/or transfer credit AND placement into MATH 51/CME 100. If 6-8 units AP or IB credit is used, must take Math 21 as neither test covers 21 content (and 21 may not be skipped using Math Diagnostic Placement results). In rare cases, a student may have covered the material in Math 21 without unit credit, and be able to present evidence of this in a petition to waive out of the course. Otherwise, taking Math 53 or CME 102 as a replacement course for 21 is allowed (since the material in 21 is built upon in these courses).
Breadth course (Math, Science, Fundamentals, & TiS) AP or transfers must be approved by the SoE Dean's office. AP approval process & transfer credit information available at https://ughb.stanford.edu/transfers-ap-exceptions . Transfer credits in Design Depth must be approved by the major advisor. Breadth (Math, Science, Fundamentals, & TiS) course AP or transfers must be approved by the SoE Dean's office. AP approval process & transfer credit information and petitions are available on the Transfers-AP-Exceptions pages.
See Courses page for additional approved Science, Fundamentals, and TiS courses. Additional math and science must be from SoE-approved list, and no further Behavioral Science courses are allowed to count toward the 30-unit math/science minimum. DESIGN 1 is required for all Design majors, but is waived as a requirement for students graduating in 2024 and 2025. It should be taken early in a student’s academic career. No prerequisites. Choose DESIGN 170: Visual Frontiers, or one 3-5-unit course from the following: DESIGN 60: Visual Expressions (new), DESIGN 172: Design Sketching and DESIGN 173: Digital Design Principles and Applications (take both if using this option), ARTSTUDI 185: Interactive Storytelling, AFRICAAM 186: Black Experimental Narrative (ARTSTUDI 186), ARTSTUDI 287: Animation II, or CS448B: Data Visualization (SYMSYS 195V). DESIGN 160R is a required one-unit advisory class taken junior year that will guide students in exploring personal and purposeful work. It is waived as a required course for students graduating in 2024. DESIGN 161A & B (ME 216B & C) together meet the Writing in the Major (WIM) requirement. Cumulative GPA for all courses within the ENGR Fundamentals and Engineering Depth categories must be at least 2.0; all courses listed must be taken for a letter grade (except those taken pandemic quarters Spring 2020-Summer 2021).
How Do I Learn More?
Discover the Major Night Recording Available
In this informational event on February 7, 2023 we talk about the vision for the program and its graduates, get into the details of the core classes, hear from the faculty representing the new Method and Domain options for students, and highlight advising resources.
Office Hours
Both faculty advisors and peers advisors will be hosting regular Office Hours sessions. Please view the current OH Schedule here. For advising questions, please email us at [email protected]. We’ll be checking messages and responding on a weekly cadence.
Petitions
Design students looking to submit a petition to deviate from any curricular requirements may navigate the following steps below. Please allow the entire petition process to take at least three weeks. Note that Domain Course Petitions are a separate form, and will be reviewed on a quarterly basis. To apply AP or IB credit towards major requirements, you may submit to the Design: Petition Form or email your completed program sheet and unofficial transcript to Darlene Lazar ([email protected]).
Step 1: Fill out an updated Program Sheet and download your Unofficial Transcript.
Design Program Sheets: Available here
Unofficial Transcript: Download from Axess
Step 2: Attend your Faculty Advisor’s Office Hours to discuss your petition.
Refer to our current Office Hours information.
Step 3: Submit your petition request to Design: Petition Form
Instructions for Declaring the Design Major
Expect for the whole declaration process to take at least 2-3 weeks depending on your preparation and planning, and your advisors’ availability.
1. Declare "Design" in Axess
2. Select a Program Sheet that overlaps your matriculation
Design Program Sheets: Available here
Unofficial Transcript: Download from Axess
3. Fill out your Program Sheet
Complete a program sheet with courses you plan to take as well as those you have already taken. List all course numbers and names along with their units (and grade, if already completed).
4. Meet with us at Office Hours
Refer to our current Office Hours information.
First attend Office Hours with a Peer Advisor to have your Program Sheet checked, and to receive your Faculty Advisor assignment.
Second attend Office Hours with your assigned Faculty Advisor to complete a final review and sign off on your Program Sheet
5. Submit your signed Program Sheet and unofficial transcript
When you are ready with your declaration materials, please submit them to our Design: Declaration Form. Student Services will complete your declaration processing in Axess. We may follow up with you if there are any questions.
| 2023-02-07T00:00:00 |
https://ughb.stanford.edu/majors-minors/design-program
|
[
{
"date": "2023/02/07",
"position": 75,
"query": "artificial intelligence graphic design"
}
] |
|
US experts warn AI likely to kill off jobs – and widen wealth ...
|
US experts warn AI likely to kill off jobs – and widen wealth inequality
|
https://www.theguardian.com
|
[
"Steven Greenhouse"
] |
Economists wary of firm predictions but say advances could create new raft of billionaires while other workers are laid off.
|
ChatGPT is just the latest technology to fuel worries that it will wipe out the jobs of millions of workers, whether advertising copywriters, Wall Street traders, salespeople, writers of basic computer code or journalists.
But while many workforce experts say the fears that ChatGPT and other artificial intelligence (AI) technologies will cause unemployment to skyrocket are overblown, they point to another fear about AI: that it will widen the US’s already huge income and wealth inequality by creating a new wave of billionaire tech barons at the same time that it pushes many workers out of better paid jobs.
Like many revolutionary technologies before it, AI is likely to eliminate jobs. But, as has been the case in the past, experts argue, AI will likely offset much of that by spurring the creation of new jobs in addition to enhancing many existing jobs. The big question is: what sort of jobs?
“AI will wipe out a lot of current jobs, as has happened with all past technologies,” said Lawrence Katz, a labor economist at Harvard. “But I have no reason to think that AI and robots won’t continue changing the mix of jobs. The question is: will the change in the mix of jobs exacerbate existing inequalities? Will AI raise productivity so much that even as it displaces a lot of jobs, it creates new ones and raises living standards?”
Anu Madgavkar, who leads labor market research at the McKinsey Global Institute, estimates that one in four workers in the US are going to see more AI and technology adopted in their jobs. She said 50-60% of companies say they are pursuing AI-related projects. “So one way or the other people are going to have to learn to work with AI,” Madgavkar said.
One way or the other people are going to have to learn to work with AI Anu Madgavkar
While past rounds of automation affected factory jobs most, Madgavkar said that AI will hit white-collar jobs most. “It’s increasingly going into office-based work and customer service and sales,” she said. “They are the job categories that will have the highest rate of automation adoption and the biggest displacement. These workers will have to work with it or move into different skills.”
In other words, many office workers could face downward mobility.
Workforce experts are asking many questions about AI: will it displace many call-center workers or merely make those workers more productive by quickly delivering needed information to them as they speak to customers? Will AI displace radiologists because of its ability to read cancer scans or will it help radiologists by enabling them to focus on more complicated, nuanced issues in interpreting scans? Will AI be able to replace some journalists by writing stories about baseball games or Wall Street’s daily ups and downs?
Some workforce experts say AI and other new technologies will hurt middle-level, white-collar jobs more than lower-paying, physically intensive jobs. McKinsey’s Madgavkar said it will be hard for AI or robots to do the jobs of janitors. In food service, she said, new technologies might be able to take customer orders, but “we’re not going to see many little robots that bring the food to a particular table”.
At law firms, AI might eliminate some attorneys’ jobs by being able to prepare first drafts of business contracts. But AI might also enable paralegals to oversee preparation of draft contracts, and that increased responsibility could mean higher pay for paralegals.
“If you make workers more productive, workers are then supposed to make more money,” said William Spriggs, an economics professor at Howard University and chief economist at the AFL-CIO, the nation’s main labor federation. “Companies don’t want to have a discussion about sharing the benefits of these technologies. They’d rather have a discussion to scare the bejesus out of you about these new technologies. They want you to concede that you’re just grateful to have a job and that you’ll pay us peanuts.”
Spriggs noted that when a wave of automation swept through the auto industry from the 1950s through 1970s, “the UAW said to Ford and GM, we’re a lot more productive and you’re a lot more profitable. As a result, the workers got a lot more money.”
David Autor, an economics professor at MIT, is wary of making predictions about ChatGPT and AI. “There’s just enormous uncertainty,” he said.
The concern is: will AI reduce the value of a lot of skill sets and make labor more commodified? David Autor,
But he’s not concerned with the US running out of jobs. “If anything, we don’t have enough people for jobs right now,” he said. “I’m concerned about the change of composition in jobs.” He voiced concern that AI, by eliminating some middle-class jobs and de-skilling some jobs, will move many workers into lower-paying jobs like food service. “The concern is: will AI reduce the value of a lot of skill sets and make labor more commodified?”
New technologies like AI often produce jobs that no one could predict – before the invention of computers, who would have foreseen the job of computer programmer? Workforce experts say AI will create more jobs for engineers and certain types of managers, and that any AI-caused decrease in jobs could be offset by increases in the number of healthcare jobs as the overall population ages. AI might call for a beefed-up system of retraining to, for instance, prepare a laid-off salesperson for a hospital job.
Juliet Schor, an economist at Boston College, said it would be far better if employers, instead of laying off people because of AI, would trim employees’ work time, perhaps to three or four days a week, instead of five. “Work-time reduction is really the far better way to respond to labor-displacing technological change,” Schor said. She voiced fears that AI could produce a large pool of jobless Americans, and even with some system of universal basic income, “that would create inequality between the people who have work and the people who don’t. That’s a big problem.”
Julie Shah, an MIT professor who leads the Interactive Robotics Group at MIT’s Computer Science and Artificial Intelligence Laboratory, said she works with employers to get them to use AI and robots to “augment and enhance workers, rather than replace them”. She said some employers want to use robots to have a lights-out factory without any human workers, while other companies want robots to work alongside humans to make them more efficient — and to have human workers on hand to propose future ideas for innovation.
Shah pointed to a study of large French corporations that introduced robots; those firms increased overall employment even as their domestic competitors reduced their workforce. She also cited a study of Canadian companies that began using robots and ultimately reduced the number of middle managers, while increasing the number of production workers. In the US, she noted, some companies adopted robots and offered higher wages, while having fewer jobs overall.
“These technologies are not leading to one future, but to many possible futures,” Shah said.
Harvard’s Katz is also worried about AI’s effects on income inequality. “It’s likely to continue to reduce labor’s share of income as many tasks get automated,” he said.
Katz said a big issue is who will share in the gains if AI yields major productivity growth, and how those gains will be shared. “How much will need to come through redistribution policies?” he asked. “If it’s really good and massively increases productivity, even if workers get a smaller share of the pie, they could end up with higher incomes.”
But these gains are unlikely to trickle down to workers in the US given current circumstances. “Having a stronger say for workers and their representatives in this process is an important element to adjusting to these changes. That’s happened in countries that have stronger unions and works councils. That’s an area where we in the US have fallen behind,” Katz said.
| 2023-02-08T00:00:00 |
2023/02/08
|
https://www.theguardian.com/technology/2023/feb/08/ai-chatgpt-jobs-economy-inequality
|
[
{
"date": "2023/02/08",
"position": 2,
"query": "automation job displacement"
},
{
"date": "2023/02/08",
"position": 1,
"query": "AI job losses"
},
{
"date": "2023/02/08",
"position": 39,
"query": "workplace AI adoption"
},
{
"date": "2023/02/08",
"position": 3,
"query": "universal basic income AI"
},
{
"date": "2023/02/08",
"position": 14,
"query": "ChatGPT employment impact"
},
{
"date": "2023/02/08",
"position": 19,
"query": "AI workers"
},
{
"date": "2023/02/08",
"position": 6,
"query": "AI layoffs"
},
{
"date": "2023/02/08",
"position": 6,
"query": "AI wages"
},
{
"date": "2023/02/08",
"position": 6,
"query": "artificial intelligence layoffs"
}
] |
Possible Solutions For The Top 5 AI Challenges We Are ...
|
Possible Solutions For The Top 5 AI Challenges We Are Already Facing
|
https://pub.towardsai.net
|
[
"Jan Marcel Kezmann"
] |
As AI becomes more advanced, it has the potential to automate certain jobs and displace human workers. This can lead to job loss and income inequality, as well ...
|
Possible Solutions For The Top 5 AI Challenges We Are Already Facing
Addressing Limitations of Bias, Transparency, Ethics, Jobs, and Security Jan Marcel Kezmann 11 min read · Feb 8, 2023 -- 1 Share
Source: Image by the author
In this blog post, I will analyze possible solutions for the top 5 challenges and limitations of artificial intelligence (AI) we will probably face in the near future and discuss strategies for addressing them.
As most of us know by now, AI has the potential to improve efficiency and revolutionize industries, but it also comes with limitations and ethical concerns that must be considered.
These challenges include bias in AI algorithms, lack of transparency in decision-making, ethical concerns, job displacement, and security vulnerabilities.
By addressing those, we can better understand how to maximize the benefits of AI and minimize its drawbacks.
Table of Contents
Biases in AI Algorithms
| 2023-02-08T00:00:00 |
2023/02/08
|
https://pub.towardsai.net/possible-solutions-for-the-top-5-ai-challenges-we-are-already-facing-7eeb0bee54de
|
[
{
"date": "2023/02/08",
"position": 23,
"query": "AI job losses"
}
] |
Bob Iger announces 7000 job cuts at Disney, signals ...
|
Bob Iger announces 7,000 job cuts at Disney, signals ‘significant transformation’
|
https://www.latimes.com
|
[
"Company Town Senior Editor",
"Ryan Faughnder Is A Senior Editor With The Los Angeles Times",
"Hollywood Inc. Team",
"Which Covers The Business Of Entertainment. He Also Launched",
"Writes The Entertainment Industry Newsletter"
] |
Bob Iger announces 7,000 job cuts at Disney, signals 'significant transformation' ... How worried should workers be about AI replacing them? July 5, 2025. LONG ...
|
Walt Disney Co. Chief Executive Bob Iger said Wednesday that the Burbank company will shed 7,000 jobs in an effort to save $5.5 billion in costs, marking some of the steepest reductions in the company’s history and the latest sign of Hollywood’s retrenchment.
The belt-tightening underscores the extraordinary difficulties Disney and other media giants face as they reckon with the realities of streaming economics — which have proved more vexing than many anticipated — and the challenges facing Iger, who took over from ousted CEO Bob Chapek in November.
Disney is facing pressure to control costs and boost profits as it continues to lose money from its key streaming business, which includes Disney+.
Advertisement
“While this is necessary to address the challenges we’re facing today, I do not make this decision lightly,” Iger said in a conference call with analysts. “I have enormous respect and appreciation for the talent and dedication of our employees worldwide, and I’m mindful of the personal impact of these changes.”
The cutbacks also reflect an uncertain economic environment, especially for entertainment, media and technology companies that expanded too aggressively during the COVID-19 pandemic. Companies including Warner Bros. Discovery, Snap, Amazon and Meta Platforms (the owner of Facebook and Instagram) have undergone significant layoffs during the last year.
The last major downsizing at Disney occurred in 2019, when the company cut thousands of jobs in the name of efficiency after its $71.3-billion acquisition of Rupert Murdoch’s 21st Century Fox.
Advertisement
According to Disney’s most recent annual report, the entertainment giant has roughly 190,000 employees, including part-time and seasonal staff.
Disney+ has made recent moves to pare its losses with price increases and a new tier with commercials. Netflix, the leader in subscription video, has also taken steps to wrangle costs and increase revenue by introducing advertising and cracking down on password sharing.
Layoffs have been expected for months, even before Iger returned to Disney.
Disney charged aggressively into the business of streaming video subscriptions, in an effort to stay relevant amid the rise of Netflix. But the effort has proved costly, with billions of dollars spent on movies and TV shows to fill the bottomless pit of demand from online viewers. Content spending became an arms race as HBO Max, Apple TV+, Peacock and Paramount+ all vied for viewers’ attention and subscription dollars.
Advertisement
Meanwhile, Disney used low pricing — starting at a bargain of $6.99 in 2019 — and promotional offers in a grab for subscribers, which also hampered profitability. Iger, on the Wednesday call, acknowledged the challenges of competition, pricing and marketing costs.
“In our zeal to go after subscribers, I think we might have gotten a bit too aggressive in terms of our promotion,” Iger said.
He did not specify where or when the layoffs will occur, but they are expected across several divisions, including an unpopular distribution unit created under Chapek.
The streaming race has been a boon for the production of new shows. But the cuts will reduce how much content Disney makes and what the company spends on its movies and shows. Iger said the company plans to examine the costs of “everything that we make” in film and TV. The company expects to deliver $3 billion in content savings “over the next few years,” he said.
Iger singled out so-called general entertainment content — shows that exist outside Disney’s signature brands — as an area he wants to “curate” heavily.
Traditional television has continued to erode, through declining ratings and accelerated cord-cutting, and streaming is a way for Disney to adapt. However, traditional distribution methods (a.k.a. cable bundles and blockbuster movies in theaters) remain profitable, unlike streaming. They’re not businesses that Disney is eager to abandon.
Advertisement
Amid all the talk of downsizing, Iger said that sequels to the “Toy Story” and “Frozen” franchises are in the works.
The company also is seeking the board of directors’ approval to restore shareholder dividends by the end of this year.
Disney’s streaming business continued to bleed cash, losing more than $1 billion during its fiscal first quarter, but the company projects the streamer will be profitable by the end of fiscal 2024.
Disney+ lost 2.4 million subscribers during the first quarter, bringing its total count down to 161.8 million, mainly stemming from declines from its Disney+Hotstar product in India. The service gained subscribers elsewhere, adding 1.4 million subscribers in the U.S. and internationally, not including Hotstar.
Overall, Disney’s streaming apps — Disney+, Hulu and ESPN+ — have 234.7 million subscribers, representing a slight increase of 1 million from October.
Disney’s financial results beat Wall Street estimates. It posted sales of $23.5 billion, up 8% from the same quarter last year. Analysts on average had been expecting $23.4 billion in revenue. Profit rose 11% to $1.28 billion. Disney’s earnings of 99 cents a share exceeded projections of 78 cents.
Advertisement
Disney shares rose 5% in after-hours trading after closing up 0.1% at $111.78 a share.
The investors call was Iger’s first since his return.
At the company’s previous earnings report, Chapek cheerfully delivered the news of strong subscriber increases at Disney+, but that masked underlying problems: disappointing profits, including at the mighty theme parks, and severe losses at the company’s streaming businesses. During the fourth quarter, streaming lost a staggering $1.5 billion for Disney.
Chapek was abruptly ousted in November by the board of directors, which brought back Iger to run the company for two years. He previously ran Disney from 2005 to 2020, a period of transformation that included the acquisitions of Pixar, Marvel and Lucasfilm.
After his return, Iger quickly moved to overhaul the company. He promised a dramatic restructuring and instituted a policy mandating that employees return to the office four days a week.
Iger laid out the details of the restructuring Wednesday. It divides the company into three units: Disney Entertainment, ESPN and Disney Parks, Experiences and Products. Studio chief Alan Bergman and TV czar Dana Walden will oversee all Disney content, except sports. ESPN, now its own distinct unit, will still be run by Jimmy Pitaro. Iger denied speculation that the separating of ESPN would lead to a sale or spinoff.
“We’re not engaged in any conversations right now or considering a spinoff of ESPN,” Iger said, while acknowledging that it had been considered in his absence.
The parks business is run by Josh D’Amaro. Bergman, Walden, Pitaro, D’Amaro and Chief Financial Officer Christine McCarthy have all been mentioned as possible successors for Iger.
Advertisement
Upon returning, Iger was quickly faced with a challenge from an influential outsider, billionaire activist investor Nelson Peltz. Peltz’s hedge fund, Trian Fund Management, which has a $900-million stake in Disney, has been lobbying the company for a seat on its board of directors, and Peltz has criticized the company for “self-inflicted” wounds, including poor succession planning and the costly acquisition of 21st Century Fox, which brought in franchises like “Avatar” but saddled the company with debt.
Peltz’s overtures have been going on since July. After being rebuffed, Peltz embarked on a proxy fight with Disney early this year, encouraging shareholders to vote for him (or his son, Matthew) to join the board and also to vote against current board director Michael Froman, a former U.S. trade representative.
Disney has been campaigning hard against Peltz, accusing him of being out of his depth when it comes to the media and entertainment business.
The company recently appointed former Nike Chief Executive Mark Parker as its next chairman, who will lead a succession-planning committee to find Iger’s replacement. During Iger’s first run as chief executive, he delayed his retirement multiple times. After handpicking Chapek as his successor, he quickly became disillusioned with the choice.
Parker replaces Susan Arnold, who is termed out after 15 years on the board.
The fight with Peltz will come to a head in early April, when Disney holds it annual shareholder meeting virtually, at which investors will vote on Disney’s 11-member board.
| 2023-02-08T00:00:00 |
2023/02/08
|
https://www.latimes.com/entertainment-arts/business/story/2023-02-08/bob-iger-first-disney-earnings-since-returning-nelson-peltz
|
[
{
"date": "2023/02/08",
"position": 98,
"query": "AI job losses"
}
] |
Winter 2023 Europe Labour Market Report: Key Takeaways
|
Winter 2023 Europe Labour Market Report: Key Takeaways
|
https://magnitglobal.com
|
[] |
The industry's first outcome-driven, AI-powered platform. Learn More ... For more key takeaways and trends in the European labor market, including ...
|
The War in Ukraine Has Impacted The Market
Contingent talent was already on the rise in Central and Eastern Europe (CEE) with contractor talent and as a nearshoring location even before war conflict began to escalate. Although the CEE talent pool is growing partially due to an influx of Ukraine refugees, the region still has significant complexities. As a result of these shifts, the competition has also increased in countries including Poland, Hungary, Romania and Czechia.
Quick Tip: To best take advantage of opportunities in CEE, companies need strong market intelligence across these locations. Without it, there could be a lack of alignment between locations, positions and rates, negating potential benefits. Also, make sure you have a comprehensive compliance program in place to manage risk when venturing into new locations.
Bottom line? The labour market in Europe will continue facing turbulence in the coming months. If businesses are looking to navigate it successfully and stay ahead, they will need to reconfigure their workforces and continue investing in contingent talent to improve their agility.
For more key takeaways and trends in the European labor market, including exclusive bill rate data on the region, check out the full report.
| 2023-02-08T00:00:00 |
https://magnitglobal.com/us/en/resources/knowledge-center/blog/winter-2023-europe-labour-market-trends.html
|
[
{
"date": "2023/02/08",
"position": 73,
"query": "AI labor market trends"
}
] |
|
IFCM20U65GD
|
IFCM20U65GD - Intelligent power modules (IPM)
|
https://www.infineon.com
|
[] |
650 V, 20 A CIPOS™ Mini 3 Phase Interleaved PFC intelligent power module (IPM) with TRENCHSTOP™ IGBT and built in NTC in MDIP-21 DCB package.
|
Registration Successful
Thanks a lot for your registration to our event. In the next minutes you will receive an email with all information and the ticket / link to the event.
| 2023-02-08T00:00:00 |
https://www.infineon.com/cms/en/product/power/intelligent-power-modules-ipm/ifcm20u65gd/
|
[
{
"date": "2023/02/08",
"position": 100,
"query": "universal basic income AI"
}
] |
|
How ChatGPT could affect the workspace
|
How ChatGPT could affect the workspace: the good, the bad and the ugly
|
https://www.thepeoplespace.com
|
[] |
We can think of how ChatGPT could affect the workplace. It could act like a virtual assistant, helping us to organise our schedules.
|
3 minute read
It’s the chatbot everyone’s talking about but will ChatGPT be a positive addition to the workplace? Not unless bias is eradicated, argues Michaela Jeffery-Morrison, CEO and co-founder of Ascend Global Media
According to an IBM study, 35% of all companies are actively using artificial intelligence in their day-to-day operations. The study also found that 42% are still exploring AI's potential for the future. Across the world of work people in senior management positions are putting time aside to seriously consider the ways in which AI could be used to help them work faster, smarter and to a higher standard.
That’s one reason why the sudden appearance of ChatGPT made waves. The chatbot, launched by OpenAI in November 2022, responds intelligently to human prompts and questions, from ‘Write me a recipe in the style of Jane Austen’ to ‘What is the meaning of life?’ Unsurprisingly, people couldn’t get enough of it. LinkedIn and Twitter feeds were filled up with ChatGPT’s responses to a wide variety of human inputs. And the consensus seemed to be that this was the ‘tipping point’: AI had officially landed.
We can think of how ChatGPT could affect the workplace. It could act like a virtual assistant, helping us to organise our schedules. It could respond to certain emails or create basic email marketing campaigns. It could be used to create first drafts of webpages, to be neatened up later by a copywriter, or provide prompts for team brainstorms to help get a conversation started.
Steven Piantadosi has shown, with a little bit of creativity ChatGPT can be made to say highly problematic things. For example, when asked for a list of the most valuable brains, broken down by race, ChatGPT returned a table with white brains (worth $5,000) at the top.
There are safeguards built into ChatGPT, but when these are bypassed – and they can be bypassed – we find that ChatGPT is not immune from the bias that affected voice assistants, for instance, or web searches, or facial recognition technology. Voice assistants, which have often reflected stereotypes of submissive female secretaries, have more difficulty understanding female voices than male ones. Even gender-neutral web searches often returned male-orientated results. And facial recognition’s accuracy is lower for women and people of colour than it is for white males
Evidently, AI is not quite ready to play a major role in the workplace, and certainly not in diversity, equity and inclusion (DEI). The technology itself is outstanding but if it is biased, then bringing it into the workplace risks entrenching tired and harmful stereotypes in subtle ways that may not even be easy to detect. While ChatGPT could, in the long term, prove to be a vital tool of hiring experts, helping potential recruits to overcome disadvantages to produce strong CVs or surmount cultural or linguistic barriers, it could, in the short term, perpetuate the kinds of problems that we’re trying – steadily but successfully – to overcome.
The solution is, of course, more diversity. The more diverse the teams that build and improve AI, the more that AI will reflect that diversity. What we want is AI that is, above all, human in its outlook. Not a specifically white, Black, male or female human, but a human. And for that to happen, we’re going to need to start paying even greater attention to representation in tech. WISE has found that just 21% of IT professionals and 12.5% of engineers are women, compared with more than half the population. And a survey at our Women of Silicon Roundabout event last year suggested that seeing and hearing from other women in tech was a major attraction, which underscores their absence at the highest levels in the sector.
The good news is that awareness of bias in ChatGPT and other forms of AI could provide us with the motivation we all need really to accelerate change in tech and increase diversity across the board. We all want to make use of the amazing developments in the space to make our lives easier and address the challenges we’re facing. If the condition for doing that effectively is to increase diversity, then we might just see companies investing heavily in doing that. There is a huge opportunity for the team that can eradicate bias from AI.
For the moment, however, we might want to hesitate before we involve technology like ChatGPT too heavily in our working lives. The progress towards DEI that we’ve made over the past few years has been fantastic. Biased AI could just undermine it.
Michaela Jeffery-Morrison, pictured below, is CEO and co-founder of Ascend Global Media
| 2023-02-08T00:00:00 |
https://www.thepeoplespace.com/ideas/articles/how-chatgpt-could-affect-workspace-good-bad-and-ugly
|
[
{
"date": "2023/02/08",
"position": 10,
"query": "ChatGPT employment impact"
}
] |
|
Afraid of ChatGPT coming for your tech job? Heed Ada ...
|
Afraid of ChatGPT coming for your tech job? Heed Ada Lovelace’s words
|
https://technical.ly
|
[
"Rajvi Mehta",
".Wp-Block-Co-Authors-Plus-Coauthors.Is-Layout-Flow",
"Class",
"Wp-Block-Co-Authors-Plus",
"Display Inline",
".Wp-Block-Co-Authors-Plus-Avatar",
"Where Img",
"Height Auto Max-Width",
"Vertical-Align Bottom .Wp-Block-Co-Authors-Plus-Coauthors.Is-Layout-Flow .Wp-Block-Co-Authors-Plus-Avatar",
"Vertical-Align Middle .Wp-Block-Co-Authors-Plus-Avatar Is .Alignleft .Alignright"
] |
This new generation of technology will make it cheaper for us to scale, increase revenue and drive impact to our world. But it can't replace a good data pro ...
|
Let’s get this out of the way: This article is written by a human being. No AI bots were harmed during the writing (except during the occasional unwanted interruptions by Alexa).
Toward the end of last year, ChatGPT took over our holiday dining tables and our 2023 vision plans as OpenAI’s launch of this “generative pre-trained transformer” hit the internet. Questions around the future of specific industries and job roles took over social media — all of while Big Tech companies laid off tens of thousands of their tech workforce.
This isn’t the first time questions about the future of technology and the job economy have been raised. Every 50 years or so, a new invention makes some practices and tools obsolete. Ada Lovelace, the first computer programmer, wrote the earliest recorded program to compute a series of numbers. She famously wrote: The analytical machine “can do whatever we know how to order it to perform. It can follow analysis, but it has no power of anticipating any analytical relations or truths.”
This sentence has stood the test of time. As technology advances, one must not fear, but embrace the idea of technology changing their careers as well as an organization’s data strategy. Per Ada Lovelace’s comment, the computer can do what we ask it to do. But the lingering gap is where the future of your data strategy lies. You need pros who are able to identify those analytical relations and truths.
If you are a data leader predicting your data strategy for the next five years, you must invest in your talent as much as you invest in your technology. Invest in data professionals who are statistically strong, and who are able to weed out insights that do not add value to the mode.
You will need distinguished and diverse talent to run your technology. A diverse workforce consists of individuals from different socioeconomic backgrounds, is inclusive of all genders and races, and is inclusive of those with non-STEM backgrounds. As tech advances, we need individuals who can bring a diversity of thought through lived experiences and world outlook to inform its development. (See: the racial bias built into some facial recognition software.)
This is where I would like aspiring data professionals to focus on building their professional brands. In 2022, venture capital investment in generative AI companies topped $1.37 billion, per PitchBook. With the rise of tools that will allow analysts and data scientists to perform their job more efficiently and with fewer errors, the need for highly skilled professionals who are able to provide valuable insights into the models’ findings will be the sweet spot.
If you are a data pro feeling uneasy with all that is going on in the hiring space, do not fret. Instead:
Go back to basics — Think of AI as your friendly calculator. It might tell you the answer to a complex math problem, but it is up to you what you do with that answer, the way you interpret that answer and tell a story will that answer will differentiate you.
— Think of AI as your friendly calculator. It might tell you the answer to a complex math problem, but it is up to you what you do with that answer, the way you interpret that answer and tell a story will that answer will differentiate you. Do your homework — Keep an eye out for the new tech stack requirements in your industry. Track different job descriptions to see what are some of the common tools that organizations use for analyzing their data. Keep in mind that although the tools might do the heavy lifting of your job in the future, you will still need to be a data translator.
— Keep an eye out for the new tech stack requirements in your industry. Track different job descriptions to see what are some of the common tools that organizations use for analyzing their data. Keep in mind that although the tools might do the heavy lifting of your job in the future, you will still need to be a data translator. Think about data privacy — The responsibility of maintaining boundaries and ethical usage of data will lie in the hands of the data talent. Be wise.
To quote Lovelace again, about the analytical machine: “Its province is to assist us in making available what we are already acquainted with.”
This new generation of technology will make it cheaper for us to scale, increase revenue and drive impact to our world. But it can’t replace a good data pro.
| 2023-02-08T00:00:00 |
2023/02/08
|
https://technical.ly/professional-development/chatgpt-data-jobs-ada-lovelace/
|
[
{
"date": "2023/02/08",
"position": 19,
"query": "ChatGPT employment impact"
}
] |
Does Your Company Need a ChatGPT Policy? Probably.
|
Does Your Company Need a ChatGPT Policy? Probably.
|
https://www.debevoise.com
|
[] |
ChatGPT is increasing employee productivity by providing support in tasks such as fact checking, document drafting, text editing, idea generation and coding ...
|
ChatGPT is increasing employee productivity by providing support in tasks such as fact checking, document drafting, text editing, idea generation and coding.
Despite its benefits, the use of ChatGPT raises legal, commercial and reputational risks, such as with privacy, consumer protection and contractual obligations.
Companies can mitigate risks associated with the use of ChatGPT through training, implementing policies on when employees are permitted to use ChatGPT for work and documenting when ChatGPT has been used in work product.
Key Takeaways:
ChatGPT is an AI-language model developed by OpenAI that was released to the public in November 2022 and already has millions of users. While most people were initially using the publicly available version of ChatGPT for personal tasks (e.g., generating recipes, poems, workout routines, etc.), many have started to use it for work-related projects. In this Debevoise Data Blog post, we discuss how people are using ChatGPT at their jobs, what are the associated risks and what policies companies should consider implementing to reduce those risks.
How Employees Are Using ChatGPT at Work
Dozens of articles have been written about how ChatGPT will replace certain jobs. But, at least for now, it appears that ChatGPT is not replacing workers, but rather, increasing their productivity. Here are some examples:
Fact-Checking : Employees are using ChatGPT in the same way that they might use Google or Wikipedia to check facts in documents that they are either producing or reviewing.
: Employees are using ChatGPT in the same way that they might use Google or Wikipedia to check facts in documents that they are either producing or reviewing. First Drafts : ChatGPT can generate drafts of speeches, memos, cover letters and routine emails. When asked to write this blog post, ChatGPT came up with several helpful suggestions, including “Employees using ChatGPT must undergo training to understand the tool’s capabilities and limitations, as well as the best practices for using it in the workplace.”
: ChatGPT can generate drafts of speeches, memos, cover letters and routine emails. When asked to write this blog post, ChatGPT came up with several helpful suggestions, including “Employees using ChatGPT must undergo training to understand the tool’s capabilities and limitations, as well as the best practices for using it in the workplace.” Editing Documents : Because it is a language model that was trained on millions of documents, ChatGPT is very good at editing text. Employees are taking poorly worded paragraphs and having ChatGPT fix grammatical errors, provide more clarity and generally increase readability.
: Because it is a language model that was trained on millions of documents, ChatGPT is very good at editing text. Employees are taking poorly worded paragraphs and having ChatGPT fix grammatical errors, provide more clarity and generally increase readability. Generating Ideas : ChatGPT is surprisingly good at generating lists. For our upcoming webcast on the role of ChatGPT in the legal profession, ChatGPT came up with questions about maintaining privilege, checking for accuracy and disclosing the role of ChatGPT to clients and courts.
: ChatGPT is surprisingly good at generating lists. For our upcoming webcast on the role of ChatGPT in the legal profession, ChatGPT came up with questions about maintaining privilege, checking for accuracy and disclosing the role of ChatGPT to clients and courts. Coding: Two of the most common uses for ChatGPT at work are generating new code and checking existing code, with many programmers saying that ChatGPT has made them much more efficient and productive.
Risks of Using ChatGPT at Work
Quality Control Risks : As impressive as it is, ChatGPT can produce inaccurate results. When drafting sections of a legal brief, it sometimes cites to cases that are irrelevant or do not exist. Because it is a language model, it often struggles with computational tasks and can give incorrect results when asked to solve basic algebra problems. OpenAI is well aware of these limitations. Indeed, ChatGPT itself often issues warnings that it might generate incorrect information. It also has gaps in its knowledge about world events that occurred after 2021. These risks may be lower when the person reviewing ChatGPT’s outputs can easily spot and correct these kinds of errors. But if the reviewer is not able to easily identify what is wrong with (or missing from) ChatGPT’s response, or there is no person reviewing it at all, then the quality control risks increase. How significant these risks are depends on the use case. For example, the risk is lower when it is summarizing news stories on a particular topic for internal awareness than it would be for generating essential code for the core operations of the company’s information systems.
: As impressive as it is, ChatGPT can produce inaccurate results. When drafting sections of a legal brief, it sometimes cites to cases that are irrelevant or do not exist. Because it is a language model, it often struggles with computational tasks and can give incorrect results when asked to solve basic algebra problems. OpenAI is well aware of these limitations. Indeed, ChatGPT itself often issues warnings that it might generate incorrect information. It also has gaps in its knowledge about world events that occurred after 2021. These risks may be lower when the person reviewing ChatGPT’s outputs can easily spot and correct these kinds of errors. But if the reviewer is not able to easily identify what is wrong with (or missing from) ChatGPT’s response, or there is no person reviewing it at all, then the quality control risks increase. How significant these risks are depends on the use case. For example, the risk is lower when it is summarizing news stories on a particular topic for internal awareness than it would be for generating essential code for the core operations of the company’s information systems. Contractual Risks : There are two primary sources of contractual risks associated with the use of ChatGPT for work. First, there may be restrictions on the company’s ability to share customers’ or clients’ confidential information with third parties including with OpenAI through ChatGPT. Second, the sharing of certain client data with ChatGPT may also violate contractual provisions with those clients regarding the purposes for which their data can be used. In conducting this analysis, companies should keep in mind that the usage rights for ChatGPT are set out in multiple documents including the Terms of Use, Sharing & Publication Policy, Content Policy, and Usage Policies, which provide that OpenAI may use content provided to ChatGPT to develop and improve its functionality. It is also important to note that many employees sign up for ChatGPT in their personal capacity, and therefore it is not entirely clear to whom these terms apply.
: There are two primary sources of contractual risks associated with the use of ChatGPT for work. First, there may be restrictions on the company’s ability to share customers’ or clients’ confidential information with third parties including with OpenAI through ChatGPT. Second, the sharing of certain client data with ChatGPT may also violate contractual provisions with those clients regarding the purposes for which their data can be used. In conducting this analysis, companies should keep in mind that the usage rights for ChatGPT are set out in multiple documents including the Terms of Use, Sharing & Publication Policy, Content Policy, and Usage Policies, which provide that OpenAI may use content provided to ChatGPT to develop and improve its functionality. It is also important to note that many employees sign up for ChatGPT in their personal capacity, and therefore it is not entirely clear to whom these terms apply. Privacy Risks : Similar to some of the contractual risks, sharing personal information about customers, clients or employees with OpenAI through ChatGPT can create privacy risks. According to the ChatGPT FAQ, OpenAI may use ChatGPT conversations for training purposes and to improve its systems. Depending on the nature of the personal information being shared with ChatGPT, companies may have obligations to update privacy policies, provide notices to customers, obtain their consent and/or provide them with opt-out rights, etc. These obligations may stem from U.S. state or federal privacy law, and companies should consider the evolving interpretation of automated decision-making, profiling and other related concepts under the 2023 state privacy laws. Uses of ChatGPT that involve personal data also raise questions about how companies—and in turn OpenAI—might approach deletion rights or requests to remove data from their ChatGPT-generated workstreams or the model itself.
: Similar to some of the contractual risks, sharing personal information about customers, clients or employees with OpenAI through ChatGPT can create privacy risks. According to the ChatGPT FAQ, OpenAI may use ChatGPT conversations for training purposes and to improve its systems. Depending on the nature of the personal information being shared with ChatGPT, companies may have obligations to update privacy policies, provide notices to customers, obtain their consent and/or provide them with opt-out rights, etc. These obligations may stem from U.S. state or federal privacy law, and companies should consider the evolving interpretation of automated decision-making, profiling and other related concepts under the 2023 state privacy laws. Uses of ChatGPT that involve personal data also raise questions about how companies—and in turn OpenAI—might approach deletion rights or requests to remove data from their ChatGPT-generated workstreams or the model itself. Consumer Protection Risks : If consumers are not aware that they are interacting with ChatGPT (as opposed to a human customer service representative), or they receive a document from a company that was generated by ChatGPT without that being clearly disclosed, there is a risk of claims of unfair or deceptive practices under state or federal law (aside from the obvious reputational risks). Depending on the circumstances, clients may be upset if they paid for content that they later learn was generated by ChatGPT but was not identified as such.
: If consumers are not aware that they are interacting with ChatGPT (as opposed to a human customer service representative), or they receive a document from a company that was generated by ChatGPT without that being clearly disclosed, there is a risk of claims of unfair or deceptive practices under state or federal law (aside from the obvious reputational risks). Depending on the circumstances, clients may be upset if they paid for content that they later learn was generated by ChatGPT but was not identified as such. Intellectual Property Risks : The use of ChatGPT raises several complex IP issues. First, to the extent that employees use ChatGPT to generate software code or other content, that content may not be protectable by copyright in many jurisdictions since it was not authored by a human being. That is currently the position of the United States Copyright Office, although the requirement for human authorship is under challenge in recently filed litigation. Second, there is risk that ChatGPT and any content it produces may be deemed a derivative work of copyrighted materials used to train the model. If that view prevails, software code, marketing materials and other content generated by ChatGPT may be found infringing, particularly if such content looks substantially similar to the copyrighted training data. In addition, to the extent that employees submit confidential code, financial data, or other trade secrets and confidential information into ChatGPT for analysis, there is a risk that other users of ChatGPT may be able to pull that same data out, thereby compromising its confidentiality and potentially supporting an argument that such data was not the subject of reasonable steps to preserve its confidential status. Finally, if software submitted to ChatGPT includes open source, it is worth considering whether such submission could be deemed to constitute a distribution that may trigger possible open source license obligations.
: The use of ChatGPT raises several complex IP issues. First, to the extent that employees use ChatGPT to generate software code or other content, that content may not be protectable by copyright in many jurisdictions since it was not authored by a human being. That is currently the position of the United States Copyright Office, although the requirement for human authorship is under challenge in recently filed litigation. Second, there is risk that ChatGPT and any content it produces may be deemed a derivative work of copyrighted materials used to train the model. If that view prevails, software code, marketing materials and other content generated by ChatGPT may be found infringing, particularly if such content looks substantially similar to the copyrighted training data. In addition, to the extent that employees submit confidential code, financial data, or other trade secrets and confidential information into ChatGPT for analysis, there is a risk that other users of ChatGPT may be able to pull that same data out, thereby compromising its confidentiality and potentially supporting an argument that such data was not the subject of reasonable steps to preserve its confidential status. Finally, if software submitted to ChatGPT includes open source, it is worth considering whether such submission could be deemed to constitute a distribution that may trigger possible open source license obligations. Vendor Risks: Many of the risks described above also apply to company data that is provided to or received from vendors. For example, should contracts with vendors specify that information provided by the vendor to the company cannot be generated by ChatGPT without prior consent? Should contracts also specify that confidential company data cannot be entered into ChatGPT?
Ways to Reduce ChatGPT Risks
Given these legal, commercial and reputational risks, some companies have started to train their employees on the proper use of ChatGPT and draft policies on the use of ChatGPT for work. Training should alert employees to the reality that ChatGPT is not perfect and results from a query to ChatGPT should still be verified using traditional means. The policies surrounding ChatGPT tend to divide ChatGPT uses into three categories: (1) uses that are prohibited (e.g., using ChatGPT to check for mistakes in confidential company or client documents, or sensitive company code); (2) uses that are permitted with authorization from some designated authority (e.g., generating code, so long as it is carefully reviewed by an expert before being implemented); and (3) uses that are generally permitted without any prior authorization (e.g., creating purely administrative internal information such as generating ideas for icebreakers for new hires). In addition, companies are taking steps to reduce the risks associated with the use of ChatGPT, including the following:
| 2023-02-08T00:00:00 |
https://www.debevoise.com/insights/publications/2023/02/does-your-company-need-a-chatgpt-policy-probably
|
[
{
"date": "2023/02/08",
"position": 39,
"query": "ChatGPT employment impact"
}
] |
|
Considerations for Using ChatGPT and Other AI Tools in ...
|
Considerations for Using ChatGPT and Other AI Tools in the Workplace
|
https://hrp.net
|
[
"Admin_Hr P"
] |
AI tools like ChatGPT have the potential to change nearly every aspect of employees' work and increase organizational efficiency. This technology is relatively ...
|
Artificial intelligence (AI) chatbot ChatGPT has recently made waves for producing human-like text and communications from user inputs. Accessible to anyone with a computer and internet connection, ChatGPT produces usable written material on a wide range of topics and helps make decisions. These functions are leading many employers to consider ways to incorporate this technology into their organizations to enhance workflows, streamline operations and improve customer experience.
Since this technology is accessible to employers of all sizes, it presents an opportunity for organizations that strategically leverage it. However, AI tools have certain limitations and potential risks that employers need to consider carefully before embracing this technology. Even if employers don’t plan on incorporating AI technology into their business operations, it’s still wise to understand these tools and their limitations because employees may use them without their employers’ knowledge or permission.
This article explains what ChatGPT is and outlines considerations for using AI technology in the workplace.
What Is ChatGPT?
ChatGPT is a natural language chatbot, meaning it uses a natural language processing system to respond in a conversational manner to user inputs. This allows it to imitate human dialogue and decision-making. ChatGPT is capable of performing or helping with a variety of tasks. For example, ChatGPT can write articles, poems and songs; perform calculations; explain difficult concepts and subjects; automate tasks; and converse with users. This technology is advancing quickly and could have a major impact on how employers run and structure their organizations.
ChatGPT is a network machine learning model trained using data sets to generate human-like text on various subjects. The chatbot is trained from books, websites and articles to create questions, answers, summaries, translations, calculations, code generation, conversations and more. Its knowledge is limited to information that was available when it was trained, and it’s unable to access new information. As a result, some of the information and answers ChatGPT provides users may be outdated or inaccurate. The current version of ChatGPT launched in November 2022 and is a free research preview. It uses approximately100 trillion machine learning parameters, but this information is current only up to 2021. OpenAI, the creator of ChatGPT, may soon offer a professional version.
Workplace Applications of AI Tools
The significance of AI technology for employers cannot be understated, as it could change almost every aspect of how organizations operate and conduct business. Many employers, especially larger ones, have been using this technology for years; however, ChatGPT is not only making this technology readily available to employers of all sizes but also more accepted than in the past.
Incorporating AI technology can enable employers to run more efficiently and economically by automating many tasks currently performed by employees. AI can not only automate and streamline manual, error-prone tasks but also augment how employees work. This could potentially change the way employees work, allowing them to focus on higher-value tasks. Instead of replacing employees’ jobs, tools like ChatGPT will likely alter the work employees do and the value they offer their employers.
Nearly every facet of an organization—including HR, marketing, accounting, legal and software engineering—could be impacted by AI technology. Specifically, this technology could change how employers operate in the following departments:
Customer support
AI chatbots can provide information and answer customer questions quickly and effectively, allowing customer support employees to focus on more important or nuanced tasks. They may also provide internal support for employees by answering questions they may have about benefits and other HR-related topics.
Sales
Sales AI technology can be used to generate sales leads, qualify prospects and guide customers through the purchase process.
Recruitment
Recruitment Employers can automate many aspects of the recruitment process, such as generating job descriptions and evaluating resumes to find qualified applicants, allowing HR teams to save time and resources.
Marketing
Marketing Tools like ChatGPT can produce usable written documents on a range of subjects. Employers can leverage this technology to create and improve their marketing efforts, including copy and content generation, search engine optimization, keyword search data and ad content optimization.
Software development
Software development AI technology can write and correct basic software code to help organizations build websites,develop apps and fix software bugs. This enables individuals without computer programming knowledge or experience to generate code.
Additionally, organizations can use this technology to help create employment policies and handbooks and calculate payroll deductions. Some AI technology can provide organizations with real-time insights into market trends and customer behavior by conducting research and data analysis.
Employer Considerations
The accessibility and capabilities of tools like ChatGPT allow employers to experiment with and assess how their organizations can benefit from incorporating this technology into their day-to-day operations. Despite the potential benefits, ChatGPT and other AI chatbots have considerable limitations that employers must consider before adopting them. While AI technology can replicate many human-like behaviors and capabilities, it lacks essential skills like critical thinking, strategic decision-making and creativity. Being aware of these limitations can help employers evaluate and determine whether to use AI technology in their workplaces.
Errors and Outdated Information
Technology like ChatGPT creates the impression that it can do more or is more reliable than it is. AI’s knowledge is limited since it’s based only on the information used to train it. Therefore, the information AI tools provide users may be low quality or outdated, or it may contain errors. As a result, employers cannot be certain that the information this technology provides or what it produces is accurate. In some cases, AI-generated errors can be costly, subjecting organizations to government audits,fines and penalties. Employers would be wise to verify the information produced by AI tools before using it.
Technological Limitations
AI models like ChatGPT require extensive training and fine-tuning to perform at levels employers need to be reliable and effective. It’s currently unclear whether ChatGPT and other AI chatbots can accurately assess the information it provides to users; thus, employers need to be cautious about using AI tools for important or consequential matters. While this technology can be a valuable resource to prepare businesses or employment-related documents and streamline processes, the information produced by AI tools should only be considered a starting point. Employers will likely still need human oversight to review information and content created by AI to evaluate its accuracy before it’s used.
Legal Considerations
Additionally, this technology can create potential legal and privacy issues employers must consider. AI-generated content can violate copyright laws and create privacy issues for organizations. For example, the conversations employees have with AI chatbots may be reviewed by AI trainers, inadvertently disclosing sensitive and confidential business information and trade secrets to third parties. This could potentially expose employers to legal risks under privacy laws. Before using AI technology,employers should consider reviewing and updating their confidentiality and trade secret policies to ensure they cover third-party AI tools. Organizations can also train employees on potential copyright and privacy issues or restrict access to AI tools to reduce legal risks.
Employer Takeaway
AI tools like ChatGPT have the potential to change nearly every aspect of employees’ work and increase organizational efficiency. This technology is relatively new, and there’s still much uncertainty surrounding it; however, it will likely continue toimprove and become more reliable over time. As such, savvy employers will closely monitor AI technology’s developments and the potential issues surrounding them.
For more workplace resources, contact HR&P today.
| 2023-06-01T00:00:00 |
2023/06/01
|
https://hrp.net/hrp-insights/considerations-for-using-chatgpt-and-other-ai-tools-in-theworkplace-2/
|
[
{
"date": "2023/02/08",
"position": 48,
"query": "ChatGPT employment impact"
}
] |
How to Stop AI From Eating Journalism
|
How to Stop AI From Eating Journalism
|
https://inthesetimes.com
|
[] |
A conversation on how the decline of unions and the rise of inequality reveals the urgent need for a revitalized labor movement. Maximillian Alvarez, Hamilton ...
|
All at once, it seems, the many dire warnings about artificial intelligence are coalescing into reality. Earlier generations of automation came for vast swaths of America’s manufacturing and service sector jobs, but now AI is coming for the “creatives” — the white collar workers who always imagined themselves insulated from such humdrum threats. No industry is at greater immediate threat than journalism. But there is a way to get ahead of this menace now, before the algorithms eat us all alive.
ChatGPT, the OpenAI program that is able to spit out coherent (if not poetic) pieces of writing, was publicly released less than three months ago. But already, media companies are rushing to experiment with ways to use the program and similar technology to replace humans on the payroll. Buzzfeed saw their wilted stock price jump after they announced they would use ChatGPT to write quizzes and listicles. Men’s Journal is using AI to spit out articles that are rewrites of old material in its archives. And CNET was quietly using AI to write stories for months before saying in late January they would “pause” the operation, after a number of the articles were found to contain errors and plagiarism.
It’s safe to say that all of this is only the beginning. Currently available AI can write (crappy) stories, draw illustrations and even replicate your voice to read text. Google is set to roll out 20 separate AI products this year. The algorithms are growing more refined by the day. Everyone working on the editorial side of journalism — writers, artists and radio reporters alike — is now competing with a computer that can produce a simulacrum of our work, for less than it costs a company to pay us. The threat to many thousands of jobs is, potentially, existential.
Is this an urgent labor issue? Certainly. But the way for media workers and their unions to fight back may not be through picket lines. The basic premise here (“new technology decimates entire existing industry at breathtaking speed”) is a familiar one. It happened to matchbook salesmen and telegraph operators and assembly line workers, and there is nothing surprising about the possibility of it happening to journalists — except for our own healthy sense of self-regard. When these stories are passed down as conventional wisdom, they are usually framed as lessons about not falling behind the fast-moving modern world; the specter of the proverbial horse-and-buggy driver is a familiar cautionary tale in American culture. The distinct lack of sympathy for the left-behind workers is in the nature of these capitalist rules of wisdom. Those horse and buggy drivers should have become auto mechanics! And laid-off journalists should learn to code! Etcetera, etcetera.
We in the journalism industry have some slight advantages over many other fields of employment. We have strong and ubiquitous unions, and we have a widely accepted code of ethics that dictates how far standards can be pushed before something no longer counts as journalism. These are the primary tools we have in our looming fight with AI. Instead of pretending that we can hold back a tidal wave of technological change by arguing that it would be bad for us, we need to focus on the more salient fact that it could be apocalyptic for journalism itself.
It’s important to note here that, for the most part, there are no agreed upon or well-established rules around AI and the ethics of journalism. The technology just hasn’t existed long enough for those rules to have come about. We better hurry up with that, or it is guaranteed that a lot of bad things will be done in the absence of industry standards. Let me suggest one bedrock rule to start with: Journalism is the product of a human mind. If something did not come from a human mind, it is not journalism. Not because AI cannot spit out a convincing replica of the thing, but because journalism — unlike art or entertainment — requires accountability for it to be legitimate.
News outlets do not just publish stories. They can also, if necessary, explain exactly how a story came about and why. Why is this news? Who were the sources? How did you draw your conclusions? How did you ensure that conflicting points of view were presented fairly? How did you determine that the headline and the lede and the anecdotes and the quotes in the story were the appropriate ones to produce the fairest and most accurate and engaging story possible? Did you leave anything out that might have gone against your thesis? Is the story improperly slanted? These are not just aesthetic questions. They are questions that news outlets must be able to answer in order for us to all agree that their journalism is justified and ethical. It is taken for granted that real journalists can answer these questions, and can make a case for their answers in the event of conflict. And one thing that all of these fundamental questions have in common is that they cannot be coherently answered by appealing to AI.
Yes, AI can spit out a sentence in response to any of these questions. But does this constitute actual transparency? When you tell an AI program to write a story, can you definitively say whether it left anything out? Can you definitively describe the process that it used to reach its conclusions? Can you definitively vouch for the fact that it was fair and accurate, and that its work is not the flawed product of any number of latent biases? No, you cannot. You don’t actually know how the AI did what it did. You don’t know the process it used to produce its work. Nor can you accurately describe or assess that process. It’s very likely that many publications will rush to use AI to churn out low-cost content, and then have a human editor look it over before its published, and use that human glance as justification for its publication. But that process is an illusion — that human editor does not and cannot ever know how the AI produced the story that it produced. The technology is, effectively, a black box. And that makes it fatally flawed in our particular field.
Human journalists are flawed too. But we are accountable. That’s the difference. Institutions in journalism live on credibility, and that credibility is granted as a direct result of the accountability that accompanies every story. When stories have errors or biases or leave things out or misstate things or bend the truth, they can be credibly challenged, and credible institutions are obligated to be able to demonstrate how and why the story is how it is, and they are obligated to acknowledge and fix any deep flaws in their reporting and writing and publishing processes on an ongoing basis. If they don’t do that, they lose their credibility. When they lose that, they lose everything. This process of accountability is the foundation of journalism. Without it, you may be doing something, but you ain’t doing journalism.
You don’t have to convince me that the media is often lazy, stupid, sensationalistic, or full of clueless Ivy League hacks making stupendously ignorant pronouncements about the world. That is why there has arisen, over the past century, a body of journalism ethics that broadly aims to make the industry accountable, and therefore credible. Accountability requires a human mind that can answer all of these questions. Because AI can never truly be accountable for its work, its work is not journalism. Because of that, publishing such work is unethical. And because of that, we must, as an industry, collectively agree to standards that ensure no news outlets publish journalism that is produced directly by AI. The technology can be a tool to assist humans in news gathering, but it should never replace any humans in a newsroom.
We are entering an era of media that will be populated by swamps full of videos and audios and photos and pieces of writing that are all completely computer-generated and designed to mislead people. If you thought all the cries of “fake news” during the Trump era were bad, just wait. The public is about to have a very, very hard time distinguishing what is real from what is fake. It is more important than ever that credible news outlets exist, and remain credible. In order to do that, we need to hold the line against AI taking over the work of human journalists. We need to unify around the idea that such a thing is not ethical. If we don’t, you can bet that companies will move as fast as possible to save a dollar — and utterly destroy journalism along the way.
| 2023-02-08T00:00:00 |
https://inthesetimes.com/article/ai-artificial-intelligence-journalism-chatgpt-media-ethics
|
[
{
"date": "2023/02/08",
"position": 12,
"query": "AI labor union"
},
{
"date": "2023/02/08",
"position": 2,
"query": "AI journalism"
}
] |
|
A More Perfect Union?: How Tech Workers' Collective ...
|
A More Perfect Union?: How Tech Workers' Collective Action Could Increase in 2023
|
https://www.law.com
|
[
"Marianna Wharry"
] |
Unionization efforts increased in 2022 in industries not historically represented, including tech, as employees and their companies grappled with changes ...
|
Unionization efforts increased in 2022 in industries not historically represented, including tech, as employees and their companies grappled with changes and challenges in the workplace in a post-pandemic environment. Observers expect that trend to gain even more momentum in 2023, spurred by younger generations of workers.
This content has been archived. Until December 31, 2025, it is available through our partners, LexisNexis® and Bloomberg Law.
Starting January 1, 2026, all archived content will be exclusively available through a subscription to Law.com NewsVault.
For information about Law.com NewsVault, please email [email protected] or click here to learn more.
Why am I seeing this?
| 2023-02-08T00:00:00 |
2023/02/08
|
https://www.law.com/2023/02/08/a-more-perfect-union-how-tech-workers-collective-action-could-increase-in-2023/
|
[
{
"date": "2023/02/08",
"position": 17,
"query": "AI labor union"
}
] |
Copyright for AI-generated works: a task for the internal market?
|
Kluwer Copyright Blog
|
https://copyrightblog.kluweriplaw.com
|
[
"University College London",
"Gowling Wlg",
"Ceyhun Necati Pehlivan",
"Nikolaus Forgó",
"Peggy Valcke",
"Marián Jankovic",
"Md. Toriqul Islam"
] |
This author poses the following question: should the internal market goal justify opening EU copyright law to AI-generated works?
|
Works generated through complex AI systems, such as machine learning and text-to-image generation models, have recently stirred up many discussions and even given rise to lawsuits (here and here). Voices emerged questioning whether current EU copyright laws should be amended in light of the many AI-generated works that have come about. One important question has been whether copyright law should be extended in order to protect such works. The academic debate has revolved mostly around copyright law rationales, the human-centred authorship requirement, as well as the notions of creativity and originality. In this upcoming paper, this author takes a different approach to this hot topic. The research positions copyright law within the EU’s constitutional limits to consider whether the EU legislative competences allow for the expansion of copyright protection to purely AI-generated works.
In EU copyright law, a central requirement for protection is human authorship and, specifically, the human’s clear stamp of free and creative choices in the final output (here and here, among many others). In many computational creativity projects in the fields of art, journalism and music, the heavy reliance on AI stretches the causation bond between the human author and the final creative output to breaking point. Consequently, it is not clear whether copyright protection would still subsist in many of these newly emerged works.
Proponents of extending copyright protection for AI-generated works suggest that absent copyright protection for such works, creativity would be stifled and various industries where purely AI-generated works are abundant will suffer underproduction. AI processes will be able to produce a large number of works extremely quickly. Faced with the choice between using an AI-generated work, which according to the status quo of EU copyright law today is likely to be free from copyright protection, and a human-authored work, for which a user needs to secure permission, some have suggested that users will prefer the former. Therefore, such AI-generated works are said to compete directly with human-authored works and thus might be capable of disturbing the market for low creativity works, which is where apparently many artists nowadays make a living.
In light of this, this author poses the following question: should the internal market goal justify opening EU copyright law to AI-generated works?
Legislative competences
Following the principle of conferral, the Union can legislate only within the limits of the competences conferred upon it by the Member States. There is no specific legal basis tackling copyright, meaning that EU copyright law-making has not been based on copyright-related reasoning, but instead on the goal of establishing an internal market as per Article 114 TFEU. To that end, the EU would typically introduce secondary copyright legislation whenever the differences between national laws risk interfering with the free movement of goods and services. All thirteen copyright directives, as well as the three regulations in the field have Article 114 TFEU as a legal basis.
Importantly, copyright law is equally about culture. However, the Union’s cultural competences, which can be found in Article 167 TFEU, are solely coordinative. Thus, culture cannot be relied on to pass harmonising measures, which is what a potential expansion for purely AI-generated works would seek to do. From a practical perspective, in terms of EU copyright law-making, this renders the culture legal basis borderline useless. On the flipside, the internal market goal’s flexible mechanics have allowed the EU legislator to present (and pass) numerous copyright measures.
Safeguarding the balanced internal market
When legislating with the internal market goal in mind, the EU has not achieved complete homogeneity of rules in many policy fields, including copyright law. Perhaps such absolute harmonisation was not always a desired end goal of the EU legislator. It would not genuinely guarantee a level-playing field for all players in all Member States in a specific market. The EU legislature must consider the overall competitive environment in each Member State and assess whether there are indeed any genuine obstacles to free movement for the internal market. Thus, as Gareth Davies has argued, balance between diversity and harmonisation is key. In achieving this balance, the EU legislator resorts to several tools: the Better Regulation Agenda, the subsidiarity and the proportionality principles.
Better Regulation
The EU has committed itself to designing policies and laws with a greater level of transparency and evidence, backed up with the views of citizens and stakeholders. This author argues that, at this stage of economic and socio-cultural research, the assumption maintained by the supporters of positive legislation is borderline speculation. Despite the vast and constantly growing literature on the intersection between copyright and AI, not a single EU-wide impact assessment has been carried out to evaluate whether European copyright law requires harmonisation at an EU level with regard to machine learning and computational creativity. Moreover, policies should not be imposed, but prepared inclusively, listening to the views of those affected by the legislation. This pertains to all stakeholders, not only those with the loudest lobby voice in Brussels. Copyright law is a public issue and as such it requires the input of the public. Such a consultation recently took place in the UK (here and here), but no such efforts have been made on an EU level. As a result, potential legislation in this field risks not only a one-sided representation of the interests of only certain stakeholders, but could also generate excessive costs (legislative, compliance, licensing, among others).
Subsidiarity and proportionality
Since the internal market is a shared competence, both the Union and the Member States may legislate and adopt legally binding acts. The limits of the Union competences in that respect are governed by the principles of subsidiarity and proportionality.
The central idea behind subsidiarity is that in areas which do not fall within the Union’s exclusive competence (so, the internal market and, hence, copyright law), the Union shall act only if and in so far as the objectives of the proposed action cannot be sufficiently achieved by the MS, but can rather, by reason of the scale or effects of the proposed action, be better achieved at a Union level. Subsidiarity may be seen as highly political and potentially ineffective. In fact, it has created no difficulties for copyright legislation.
Proportionality instead may act as a major barrier for any potential legislation in this field. It requires that whatever measure is proposed at an EU level must be proportionate to the interest pursued. In other words, let us not kill a fly with an elephant gun. Generally, it entails three steps:
assessment of the suitability of the measure for the attainment of the objective (the appropriateness principle); evaluation of the necessity of the measure (are there other, equally suitable, less restrictive measures capable of attaining the same objective); and balancing the negative impact of the restrictions imposed against the added value (proportionality stricto sensu).
Applying this to the AI/copyright scenario, the suitability test requires that copyright law be the most appropriate measure to attain the objective at stake. Thus, copyright protection would be suitable if there is an existing or imminent obstacle to trade in the context of AI-generated works and if left in the public domain, the functioning of the internal market would be disturbed. As above, at this stage of research, there is not enough evidence to support this assertion, so it is questionable whether the suitability test will be met. Nonetheless, even if such evidence emerges, the necessity test, namely the second factor, is what could present more serious obstacles to pass legislation of this kind. Copyright protection must be the least restrictive measure to achieve the said objective. Here, potentially significant challenges emerge with respect to copyright duration, which is particularly long, and its scope, whereby economic rights have traditionally been interpreted broadly. AI processes can generate a large number of literary, musical and artistic works in the span of several seconds. In light of the term of protection, if these works are automatically covered by copyright law, then the public domain will inevitably be jeopardised, and for a very long time. This brings the discussion to the third factor – proportionality stricto sensu. It is essential to consider and respect the interests of stakeholders other than the AI creation and dissemination teams. An open and inclusive public discussion on copyright and AI via public consultations is essential and it appears that here it is absent.
Conclusion
In sum, should copyright law be extended to protect AI-generated works, the proportionality principle must necessarily step in and ensure that the EU measure does not lead to over-protection, an eventual “tragedy of anticommons” and overexploitation of authorial rights. Unfortunately, in practice, it is questionable whether and to what extent these important constitutional safeguards would have a real effect. Subsidiarity and proportionality have often been criticised for being mere methods of window dressing. Like Stephen Weatherill argues with reference to the proportionality principle, “only legislative choices that verge on the absurd are likely to be condemned as manifestly inappropriate”.
This blogpost is based on a forthcoming article by the author which is accepted for publication in the European Law Review and will be available in April 2023. For further information, please contact the author directly.
| 2023-02-08T00:00:00 |
2023/02/08
|
https://copyrightblog.kluweriplaw.com/2023/02/08/copyright-for-ai-generated-works-a-task-for-the-internal-market/
|
[
{
"date": "2023/02/08",
"position": 32,
"query": "AI labor union"
}
] |
How Effective is AI in Education? 10 Case Studies and ...
|
How Effective is AI in Education? 10 Case Studies and Examples
|
https://axonpark.com
|
[
"Nikita Verma"
] |
A study by Knewton, an adaptive learning company, found that students using their AI-powered adaptive learning program improved their test scores by 62% ...
|
99.4% of 509 higher education institutions in the US say that artificial intelligence (AI) in education and learning will be instrumental to their institution’s competitiveness in the next three years.
In a world where technology is advancing at an unprecedented pace, it’s no surprise that AI is making its way into the classroom. As educators and researchers continue to explore the possibilities of AI in education, they are discovering its potential to revolutionize the way we learn. The AI education market is predicted to cross 20 billion USD by 2027.
In this article, we will explore some real-life examples of how AI is being used to improve education and how it can help students succeed.
1. 80% accurate recommendations to help students, when compared to expert human advice
A Stanford researcher developed an AI program to provide students with assistance when they get stuck in self-paced digital learning. The study tested a machine-learning program that would predict when a student was likely to get stuck and start “wheel-spinning”, at which point it would recommend a relevant solution. The program was trained by analyzing performance data from 1,170 Ugandan school children who had used tablets to learn English reading skills through videos and mini-games. The program was able to predict whether a child would fall into “wheel-spinning”, even before they had begun a new lesson.
In four out of the six cases, the model and the human expert came up with the same recommendations. The study concludes that AI can be used to identify student problems and make it easier for a limited number of human teachers to help a large number of students.
2. With 91% accuracy, AI-enhanced Chatbots provided personalized help and guidance to students
The University of Murcia in Spain recently implemented an AI-powered chatbot to assist students with inquiries about the campus and academic programs. To the surprise of administrators, the chatbot demonstrated a high level of proficiency, answering over 38,708 questions correctly more than 91% of the time. Keep in mind, this was before ChatGPT, and we can only expect these metrics to improve even further.
This implementation not only provided students with prompt responses outside of standard office hours but also resulted in an increase in student motivation. Additionally, the implementation of the chatbot did not require any changes to the existing staff structure.
3. 62% Increase in Test Scores Through Adaptive Learning
A study by Knewton, an adaptive learning company, found that students using their AI-powered adaptive learning program improved their test scores by 62% compared to students who did not use the program. The program provided personalized feedback and instruction to students, tailoring the learning experience to their individual needs and abilities.
4. AI Improved Students’ Grades by 30% While Reducing Their Anxiety by 20%
Pai et al. (2020) proposed an intelligent tutoring system to help fifth-grade students learn the mathematical unit of multiplication and division. They found that the intelligent tutoring system (ITS) improved students’ mathematics learning performance and increased their learning motivation.
5. Over 47% of Learning Management Tools Will Be Powered by AI in the Following Three Years
It is projected that nearly 47% of learning management tools will incorporate AI by 2024. This will enable teachers to personalize education for each student by utilizing the core curriculum and supplementing it with various materials, facilitated by the assistance of AI.
The market for these AI-enhanced e-Learning tools is anticipated to reach over $6 billion by 2024. Again this survey was conducted prior to the proliferation of AI tools like ChatGPT over the last few months, therefore we think it’s likely that this statistic could be even larger than originally predicted.
6. With a 97% Success Rate, AI Teaching Assistant Answers 10,000 Messages a Semester
At the Georgia Institute of Technology, an AI-powered chatbot named Jill Watson, developed by IBM’s Watson, was employed as a teaching assistant for a course with 300 students.
With a 97% accuracy rate, Jill Watson was able to respond to around 10,000 student inquiries each semester with remarkable human-like efficiency.
7. AI Predicts a Student’s Final Grade with 80% Accuracy, to Save 34,712 Students From Failing
Ivy Tech Community College in Indiana conducted a pilot study using data from 10,000 course sections. By identifying 16,000 students at risk of failing within the first two weeks of the semester, the college was able to address non-academic obstacles that contributed to their struggles.
By the end of the semester, 3,000 students were saved from failing – 98% of the contacted students obtained a C grade or better. Through Project Student Success, the college has been able to assist 34,712 students and counting.
8. 95% of graduates with hearing impairments are successfully employed, thanks to AI-assisted education
Text-to-speech and speech-to-text technology are being used to make learning materials more accessible to students with visual and hearing impairments. National Technical Institute for the Deaf (NTID) at RIT serves more than 1,100 deaf and hard-of-hearing students from around the United States and the world, allowing students to access and engage with learning materials in a way that is comfortable and convenient for them.
9. Over 800,000 students across Latin America, Korea, and Japan have improved their English by practicing with AI voice technology
Edwin is an AI-powered service for learning English as a foreign language. To provide affordable, personalized, 1:1 learning, it combines adaptive learning and Natural Language Understanding technologies with pedagogical content.
Using adaptive learning technology, Edwin’s team built English test preparation courses that were taught by a Facebook chatbot and a human teacher in tandem. Over 800,000 students have improved their English with Edwin.
10. Educators Spend 70% Less Time Grading Assignments By Using an AI-Powered Grading Tool
Gradescope is a platform designed to streamline the grading process, delivering benefits to both educators and students.
The AI tech was shown to reduce the amount of time teachers spent on grading by 70%. The platform operates by allowing students to upload their assignments, which are then sorted and grouped by Gradescope. Educators have access to per-question and per-rubric statistics, providing valuable insights into student performance.
AI in Education: A Gateway to a Better Future of Learning
The above are just a small handful of examples to demonstrate the power of AI for education. Given the recent explosion of AI tools into the market, this is just the beginning of what is certain to be a transformative time for education and learning. At Axon Park, we’ve been exploring the use of AI in education since 2019, and look forward to sharing our latest work with you all over the coming days.
If you come across any great statistics that have recently been released, and you think they should be added to this list, please don’t hesitate to reach out.
| 2023-02-08T00:00:00 |
2023/02/08
|
https://axonpark.com/how-effective-is-ai-in-education-10-case-studies-and-examples/
|
[
{
"date": "2023/02/08",
"position": 2,
"query": "AI education"
},
{
"date": "2023/02/08",
"position": 7,
"query": "artificial intelligence education"
}
] |
'There is no standard': investigation finds AI algorithms ...
|
‘There is no standard’: investigation finds AI algorithms objectify women’s bodies
|
https://www.theguardian.com
|
[
"Gianluca Mauro",
"Hilke Schellmann"
] |
Images posted on social media are analyzed by artificial intelligence ... Two Guardian journalists used the AI tools to analyze hundreds of photos of ...
|
Images posted on social media are analyzed by artificial intelligence (AI) algorithms that decide what to amplify and what to suppress. Many of these algorithms, a Guardian investigation has found, have a gender bias, and may have been censoring and suppressing the reach of countless photos featuring women’s bodies.
These AI tools, developed by large technology companies, including Google and Microsoft, are meant to protect users by identifying violent or pornographic visuals so that social media companies can block it before anyone sees it. The companies claim that their AI tools can also detect “raciness” or how sexually suggestive an image is. With this classification, platforms – including Instagram and LinkedIn – may suppress contentious imagery.
Objectification of women seems deeply embedded in the system Leon Derczynski, IT University of Copenhagen
Two Guardian journalists used the AI tools to analyze hundreds of photos of men and women in underwear, working out, using medical tests with partial nudity and found evidence that the AI tags photos of women in everyday situations as sexually suggestive. They also rate pictures of women as more “racy” or sexually suggestive than comparable pictures of men. As a result, the social media companies that leverage these or similar algorithms have suppressed the reach of countless images featuring women’s bodies, and hurt female-led businesses – further amplifying societal disparities.
Even medical pictures are affected by the issue. The AI algorithms were tested on images released by the US National Cancer Institute demonstrating how to do a clinical breast examination. Google’s AI gave this photo the highest score for raciness, Microsoft’s AI was 82% confident that the image was “explicitly sexual in nature”, and Amazon classified it as representing “explicit nudity”.
View image in fullscreen Microsoft’s AI was 82% confident that this image demonstrating how to do a breast exam was ‘explicitly sexual in nature’, and Amazon categorized it as ‘explicit nudity’. Photograph: National Cancer Institute/Unsplash
Pregnant bellies are also problematic for these AI tools. Google’s algorithm scored the photo as “very likely to contain racy content”. Microsoft’s algorithm was 90% confident that the image was “sexually suggestive in nature”.
View image in fullscreen Images of pregnant bellies are categorized as ‘very likely to contain racy content’. Photograph: Dragos Gontariu/Unsplash
“This is just wild,” said Leon Derczynski, a professor of computer science at the IT University of Copenhagen, who specializes in online harm. “Objectification of women seems deeply embedded in the system.”
One social media company said it did not design its systems to create or reinforce biases and classifiers are not perfect.
“This is a complex and evolving space, and we continue to make meaningful improvements to SafeSearch classifiers to ensure they stay accurate and helpful for everyone,” a Google spokesperson said.
Getting shadowbanned
In May 2021, Gianluca Mauro, an AI entrepreneur, adviser and co-author of this article, published a LinkedIn post and was surprised it had just been seen 29 times in an hour, instead of the roughly 1,000 views he usually gets. Maybe the picture of two women wearing tube tops was the problem?
He re-uploaded the same exact text with another picture. The new post got 849 views in an hour.
View image in fullscreen Mauro’s LinkedIn post showing two women in tube tops received only 29 views in one hour compared to 849 views when a different image was used. Composite: Gianluca Mauro/The Guardian
It seemed like his post had been suppressed or “shadowbanned”. Shadowbanning refers to the decision of a social media platform to limit the reach of a post or account. While a regular ban involves actively blocking a post or account and notifying the user, shadowbanning is less transparent - often the reach will be suppressed without the user’s knowledge.
The Guardian found that Microsoft, Amazon and Google offer content moderation algorithms to any business for a small fee. Microsoft, the parent company and owner of LinkedIn, said its tool “can detect adult material in images so that developers can restrict the display of these images in their software”.
Another experiment on LinkedIn was conducted to try to confirm the discovery.
View image in fullscreen The photo of the women got eight views in one hour, while the picture with the men received 655 views, suggesting the women’s photo was either suppressed or shadowbanned. Composite: Gianluca Mauro/The Guardian
In two photos depicting both women and men in underwear, Microsoft’s tool classified the picture showing two women as racy and gave it a 96% score. The picture with the men was classified as non-racy with a score of 14%.
The photo of the women got eight views within one hour, and the picture with the two men received 655 views, suggesting the photo of the women in underwear was either suppressed or shadowbanned.
You cannot have one single uncontested definition of raciness Abeba Birhane
Shadowbanning has been documented for years, but the Guardian journalists may have found a missing link to understand the phenomenon: biased AI algorithms. Social media platforms seem to leverage these algorithms to rate images and limit the reach of content that they consider too racy. The problem seems to be that these AI algorithms have built-in gender bias, rating women more racy than images containing men.
“Our teams utilize a combination of automated techniques, human expert reviews and member reporting to help identify and remove content that violates our professional community policies,” said a LinkedIn spokesperson, Fred Han, in a statement. “In addition, our feed uses algorithms responsibly in order to surface content that helps our members be more productive and successful in their professional journey.”
Amazon said content moderation was based on a variety of factors including geography, religious beliefs and cultural experience. However, “Amazon Rekognition is able to recognize a wide variety of content, but it does not determine the appropriateness of that content,” an Amazon spokesperson said. “The service simply returns labels for items it detects for further evaluation by human moderators.”
Digging deeper
Natasha Crampton, Microsoft’s chief responsible AI officer, and her team began investigating when journalists notified her about the labeling of the photos.
“The initial results do not suggest that those false positives occur at a disproportionately higher rate for women as compared with men,” Crampton said. When additional photos were run through the tool, the demo website had been changed. Before the problem was discovered, it was possible to test the algorithms by simply dragging and dropping a picture. Now an account needed to be created and code had to be written.
View image in fullscreen Screenshots of Microsoft’s platform in June 2021 (left), and in July 2021 (right). In the first version, there is a button to upload any photo and test the technology, which has disappeared in the later version. Composite: Gianluca Mauro/The Guardian
But what are these AI classifiers actually analyzing in the photos? More experiments were needed, so Mauro agreed to be the test subject.
When photographed in long pants and with a bare chest, Microsoft’s algorithm had a confidence score lower than 22% for raciness. When Mauro put on a bra, the raciness score jumped to 97%. The algorithm gave a 99% score when the bra was held next to me.
“You are looking at decontextualized information where a bra is being seen as inherently racy rather than a thing that many women wear every day as a basic item of clothing,” said Kate Crawford, professor at the University of Southern California and the author of Atlas of AI.
Abeba Birhane, a senior fellow at the Mozilla Foundation and an expert in large visual datasets, said raciness is a social concept that differs from one culture to the other.
“These concepts are not like identifying a table where you have the physical thing and you can have a relatively agreeable definition or rating for a certain thing,” she said. “You cannot have one single uncontested definition of raciness.”
Why do these systems seem so biased?
Modern AI is built using machine learning, a set of algorithms that allow computers to learn from data. When developers use machine learning, they don’t write explicit rules telling computers how to perform a task. Instead, they provide computers with training data. People are hired to label images so that computers can analyze their scores and find whatever pattern helps it replicate human decisions.
Margaret Mitchell, chief ethics scientist at the AI firm Hugging Face and former co-head of Google’s Ethical AI research group, believes that the photos used to train these algorithms were probably labeled by straight men, who may associate men working out with fitness, but may consider an image of a woman working out as racy. It’s also possible that these ratings seem gender biased in the US and in Europe because the labelers may have been from a place with a more conservative culture.
Ideally, tech companies should have conducted thorough analyses on who is labeling their data, to make sure that the final dataset embeds a diversity of views, she said. The companies should also check that their algorithms perform similarly on photos of men v women and other groups, but that is not always done.
“There’s no standard of quality here,” Mitchell said.
This gender bias the Guardian uncovered is part of more than a decade of controversy around content moderation on social media. Images showing people breastfeeding their children and different standards for photos of male nipples, which are allowed on Instagram, and female nipples, which have to be covered, have long garnered outcries about social media platforms’ content moderation practices.
Now Meta’s oversight board – an external body including professors, researchers and journalists, who are paid by the company – has asked the tech giant to clarify its adult nudity and sexual activity community standard guidelines on social media platforms “so that all people are treated in a manner consistent with international human rights standards, without discrimination on the basis of sex or gender”.
Meta declined to comment for this story.
‘Women should be expressing themselves’
Bec Wood, a 38-year-old photographer based in Perth, Australia, said she was terrified of Instagram’s algorithmic police force.
I will censor as artistically as possible any nipples. I find this so offensive to … women Bec Wood
After Wood had a daughter nine years ago, she started studying childbirth education and photographing women trying to push back against societal pressures many women feel that they should look like supermodels.
“I was not having that for my daughter,” she said. “Women should be expressing themselves and celebrating themselves and being seen in all these different shapes and sizes. I just think that’s so important for humanity to move forward.”
Wood’s photos are intimate glimpses into women’s connections with their offspring, photographing breastfeeding, pregnancy and other important moments in an artful manner. Her business is 100% dependent on Instagram: “That’s where people find you,” Wood said. “If I don’t share my work, I don’t get work.”
View image in fullscreen Google and Microsoft rated Wood’s photos as likely to contain explicit sexual content. Amazon categorized the image of the pregnant belly on the right as ‘explicit nudity’.
Since Wood started her business in 2018, for some of her photos she got messages from Instagram that the company was either taking down some of her pictures or that they were going to allow them on her profile but not on the explore tab, a section of the app where people can discover content from accounts they don’t follow. She hoped that Instagram was going to fix the issue over time, but the opposite happened, she said. “I honestly can’t believe that it’s gotten worse. It has devastated my business.” Wood described 2022 as her worst year business-wise.
She is terrified that if she uploads the “wrong” image, she will be locked out of her account with over 13,000 followers, which would bankrupt her business: “I’m literally so scared to post because I’m like, ‘Is this the post that’s going to lose everything?’” she said.
To avoid this, Wood started going against what made her start her work in the first place: “I will censor as artistically as possible any nipples. I find this so offensive to art, but also to women,” she said. “I almost feel like I’m part of perpetuating that ridiculous cycle that I don’t want to have any part of.”
Running some of Wood’s photos through the AI algorithms of Microsoft, Google and Amazon, including those featuring a pregnant belly got rated as racy, nudity or even explicitly sexual.
Wood is not alone. Carolina Are, an expert on social media platforms and content moderation and currently an Innovation fellow at the Centre for Digital Citizens at Northumbria University said she has used Instagram to promote her business and was a victim of shadowbanning.
Are, a pole dance instructor, said some of her photos were taken down, and in 2019, she discovered that her pictures did not show up in the explore page or under the hashtag #FemaleFitness, where Instagram users can search content from users they do not follow. “It was literally just women working out in a very tame way. But then if you looked at hashtag #MaleFitness, it was all oily dudes and they were fine. They weren’t shadowbanned,” she said.
View image in fullscreen Carolina Are, a pole dance instructor, found that some of her photos were not showing up on social media. Photograph: Rachel Marsh/Courtesy of @ray.marsh
For Are, these individual problems point to larger systemic ones: many people, including chronically ill and disabled folks, rely on making money through social media and shadowbanning harms their business.
Mitchell, the chief ethics scientist at Hugging Face, these kinds of algorithms are often recreating societal biases: “It means that people who tend to be marginalized are even further marginalized – like literally pushed down in a very direct meaning of the term marginalization.”
It’s a representational harm and certain populations are not adequately represented, she added. “In this case, it would be an idea that women must cover themselves up more than men and so that ends up creating this sort of social pressure for women as this becomes the norm of what you see, ” Mitchell said.
The harm is worsened by a lack of transparency. While in some cases Wood has been notified that her pictures were banned or limited in reach, she believes Instagram took other actions against her account without her knowing it. “I’ve had people say ‘I can’t tag you,’ or ‘I was searching for you to show my friend the other day and you’re not showing up,’” she said. “I feel invisible.”
Because she might be, said computer scientist Derczynski: “The people posting these images will never find out about it, which is just so deeply problematic.” he said. “They get a disadvantage forced upon them and they have no agency in this happening and they’re not informed that it’s happening either.”
| 2023-02-08T00:00:00 |
2023/02/08
|
https://www.theguardian.com/technology/2023/feb/08/biased-ai-algorithms-racy-women-bodies
|
[
{
"date": "2023/02/08",
"position": 62,
"query": "AI journalism"
}
] |
HR Automation: How AI is Changing The Game
|
HR Automation: How AI is Changing The Game
|
https://gleematic.com
|
[
"Fauzul Fahmi"
] |
AI-powered recruitment tools, for example, can help HR professionals identify the best candidates for open positions by analyzing resumes and conducting ...
|
Have you been implementing HR automation? Or you are unaware that it is being the future of human resources that most HR have been doing?
Human resources management (HRM) is a critical function of any organization, responsible for recruiting, hiring, and developing employees. As technology continues to advance, the field of HRM is increasingly turning to artificial intelligence (AI). The objective is to improve efficiency and effectiveness.
According to report by Oracle, most HR practitioners welcome the integration of AI into their HR processes. The report stated that AI is changing the relationship between people and technology at work. This will support more areas where HR can implement AI technologies. One of many is AI-powered automation, or also known as intelligent automation or cognitive automation. Based on Gartner, 47% of businesses will use some sort of AI in their HR processes in the upcoming years.
AI-powered recruitment tools, for example, can help HR professionals identify the best candidates for open positions by analyzing resumes and conducting initial interviews. These tools can also help to reduce bias in the hiring process by eliminating the need for human judgment in certain stages of the process.
How AI can Change The Game with HR Automation
Additionally, AI can assist with onboarding and training new employees by providing personalized learning experiences. This can help to ensure that new hires are able to quickly become productive members of the organization.
As employees progress in their careers, AI can also be used to help identify potential leaders and high-potential employees. This can help organizations to identify and groom future leaders, ensuring continuity and success in the long-term.
Another area where AI can be beneficial is in the management of employee performance. By analyzing data on employee performance, AI can help managers to identify areas where employees may need additional training or support. This can lead to improved employee engagement and productivity.
AI can also be used to manage employee benefits and compensation. By analyzing data on employee compensation and benefits, AI can help organizations to ensure that they are providing competitive packages that will help to attract and retain top talent.
In addition to these benefits, AI can also help organizations to improve their compliance with labor laws and regulations. By automating certain processes and monitoring employee data, AI can help companies to ensure that they are in compliance with all relevant laws and regulations.
Automation and AI: A Perfect Partner for HR Automation
However, it’s important to note that AI is not a replacement for human HR professionals. While AI can assist with certain tasks and processes, HR professionals are still needed to provide strategic direction and make important decisions.
As such, organizations need to strike a balance between using AI to improve efficiency and effectiveness, while also ensuring that human expertise and judgment are still present in the process.
Overall, the integration of AI in human resources management can bring about many benefits for the organizations, from recruitment, onboarding, employee development, compliance, and even performance management. It’s important for organizations to consider how they can best utilize AI to improve their HR processes and achieve their overall business goals.
Read about how to use Artificial Intelligence solutions for Human Resources
The Benefits of HR Automation
We always talk about increasing productivity, streamlining current workflow that is too time-consuming, improving efficiency – as main objectives when we want to implement AI-automation. Yes, it is correct – but how can these automation impact specifically on each process?
1. Eliminating time-consuming administrative tasks
According to HR University, HR staff whose core tasks are administrative, ensure that HR department is inputting their data records and preparing (handling) HR documents correctly. They will need to do record-keeping, do analytics and reporting, documentation, updating and integrating data between various sources.
Administrative tasks are the example of “recurring” tasks. Recurring tasks, or often called repetitive tasks, are activities that you have to do over and over again. These tasks are mainly the core activities within your job description that comes repeatedly, and you have to deal with them in regular time intervals – can be daily, weekly, or monthly basis. These recurring tasks are monotonous and low-level, that you can actually improve to save more time, cost, and energy.
According to Gartner, 56% of companies using AI for HR are trying to automate repetitive tasks. Incorporating AI cognitive functions with robotic process automation can improve HR processes, as this technology can eliminate time-consuming administrative tasks. For example, the smart robots can help to automate recruitment process – and only need HR staff intervention on interviewing potential candidates, or in verification of validation step. The smart robots, with the help of AI, can have document “understanding” that they can process documents – which HR would have been having trouble with, considering there must be employee-related documents to process and record-keeping each day.
With the robots being focus in automating these administrative tasks, this leaves opportunity for HR to focus more on tasks that can bring more value to the company and employees – or any tasks that are more strategic.
2. Improved recruitment process, better talent acquisition
It’s just not candidates who are in competition to get a job, but it’s also a competition between companies to acquire best potential candidates as their employees. This will burden HR, in a way that HR needs to invest a huge time and effort in finding the best potential candidates that fit what the company needs. If HR is being too overwhelmed with never-ending administrative tasks, they can not be entirely focus on finding the best talent. Taking too long to find best candidate means HR is losing its potential ones to the other companies that could be their competitors.
Accelerating Recruitment Process with HR Automation
According to IQ Partners, 57% of companies plan to accelerate the recruitment process. On their report, they stated that traditional recruitment is no longer effective for HR to implement. On the survey they have done, companies who participated in the survey said that they have identified a number of ways to help improve the talent acquisition process:
75% plan to adopt new technologies to attract highly skilled employees
to attract highly skilled employees 57% plan to speed up the talent acquisition process
62% plan to recruit talent that can work faster and more efficiently
With 75% plan to adopt new technologies, we can take example from how AI-automation can transform recruitment process in HR. The smart robot can help HR to spread the word about the open recruitment, filter applicants based on criteria set by end-users, monitor assignments given by end-users to the candidates and become the bridge between candidates and HR recruiter, and do reporting.
According to G2, 80% of job seekers said they would be dissuaded from considering other job openings at a company that did not give them any status on their application. The smart robots will not just help HR by automating recruitment process, but also in providing feedback or status to the rejected applicants.
3. Faster and more efficient in onboarding employee
How HR onboards their new employees will certainly leave first-impression to those employees on how efficient HR works. Thus, onboarding process plays a crucial part for not just HR, but also how they contribute to employee’s satisfaction.
Based on Nucleus Research, companies that do use HR automation said their onboarding process was 67% faster. However, according to G2, the lack of onboarding automation tools hinder HR for their onboarding processes. Arising as HR automation tool, AI-powered automation has all it takes to be considered as the perfect tool to improve onboarding process.
HR automation with AI offers faster and more efficient employee onboarding process:
Verifying employment documentation: contracts, ID cards, resume/CV, etc.
Manage access hand-over for software, hardware, accounts, etc. that employees might need for their work
Deliver company policies and procedures in compliance
Help HR admin to enter new employee data on HR system (e.g. payroll system)
4. Employee-driven insights & better employee retention
A.I Machine Learning has the ability to give us recommendations and help us to do cognitive decision-making, despite being done by the robots. This capability allows us to generate employee-driven insights, that we can use to engage employees better to prevent the high turnover – or, in nutshell, improve employee retention.
A.I Natural Language Processing can also help to do sentiment analysis when HR is doing survey on employee satisfaction. Statistics show that 20% of new hires leave the company to get better opportunities within the first 45 days of work. Therefore, collecting employee feedback on their satisfaction with the onboarding process and new jobs can help identify potential problems.
Artificial intelligence (AI) makes this process much easier and more efficient. Cognitive Automation software may send out surveys after the first week, first month, or first quarter of a job. In addition, Machine Learning (ML) can reveal latent dissatisfaction with survey results to prevent employee attrition.
AI analytics tools have the ability to examine collected and processed data in ways no human administrator could ever do. Human resources and wage management cover a constantly changing regulatory landscape worldwide. AI technology has the potential to address many of the human resources challenges such as payroll management, attrition management, and so on. This allows the company to calculate turnover before it happens. If the robot detects a risk of escape, it will send alerts to the hiring manager or staff to help them solve the problem.
5. Higher chance for employee engagement and upskilling
Having a thorough employee-driven insights, such as areas HR can improve to increase employees’ satisfaction, will not just boost employee retention but HR can also engage their employees better. HR can also find out areas employees are looking forward for upskilling themselves.
HR can also use AI-powered automation to track employees’ KPI. This option involves providing an automated checklist of all the tasks and goals that a new employee needs to complete upon onboarding, such as reading and signing certain documents, taking tests, or creating collaboration projects. HR can also set deadlines on the system and send a notification when the date is approaching. HR can also get some important indicators of the work done.
Examples of HR Automation
According to the report by Forbes, AI adopters are 19% more effective in reducing the time HR spends on administrative tasks.
Here are some use-cases where HR can leverage on AI-powered automation to automate some of their processes:
1. Extracting Data from Resume/CV
According to a study by G&A Partners, human resources departments spend 73 percent of their time on administrative tasks. While the HR department wants to focus on programs to improve work performance and productivity, much remains to be done. There are still documents that are missing or out of date, forms that need to be filled in.
In below video, cognitive bot can handle resume/CV received by the hiring team. The smart robot can ‘read’ the resumes despite the complexity of its template or form of document, thus can also intelligently identify and extract key data points. After extracting the resumes of potential candidates, the robot will put the data in a spreadsheet. Furthermore, the robot will send the spreadsheet by email to the rest of hiring team for a review.
HR Process Automation: Automating Recruitment Process | Intelligently Read & Extract Resumes
Save to Your Reading List: What Is Intelligent Document Processing (IDP)?
2. Automating Recruitment Process
Recruitment is core activity in HR department – which is a long complicated process that is so consuming both of effort, cost, and time. But if HR staff can find a right tool to automate this complicated process and eliminate its complexity, it can really bring benefits to the company in terms of productivity and efficiency.
In this video, the smart robot can automate the recruitment process. The robot can access job or recruitment portal to check candidates who apply to the position, collect their data to the internal document, and shortlist candidates based on recruiter’s criteria. Cognitive bots proceed to process initial assessment of candidates by sending them email and gradually checks if they have completed the assessment phase. Human staff in HR department only has to review assessment document completed by potential candidates.
Replace Manual Hiring Process with Automation
3. Data Integration on Payroll System
Imagine having to do recurring tasks every time there’s an employee to onboard. Extracting data from documents for their personal data verification and authentication is one of the painful task, but what’s more painful is having to enter and update their data on payroll system.
In this video, the smart robot can help to automate one of core processes that HR department has: updating employee details on the payroll system. There will always be changes in data and the data stored in the system needs to be updated accordingly. If this process is done manually, it can be painful to the human-staff considering how time consuming it is.
HR Process Automation: Data Integration on Payroll System
4. Recruitment Reporting
In this video, the smart robot can get data from multiple job application forms in a Microsoft Excel file, and enter all of the data into a different Microsoft Excel file. The robot can copy all the data from multiple sheets in an Excel file, and paste it into another Excel file. This function will be useful in making HR recruitment report for the HR manager to review.
HR Recruitment Reporting
5. Predict HR Attrition Rate
Empowered by A.I. Machine Learning, cognitive bots can perform predictive analysis to prevent employee attrition. With predictive analysis, the robot can accurately predict the attrition rate of employees based on their employment records. Moreover, the robot can also predict who will likely to leave, why employees tend to leave, and analyze the key-risk factors affecting the high employee turn-over. With this capability, the robot can enlighten the human resource department to improve the way they engage loyal employees to stay in the company/organization.
Machine Learning in Predictive Analysis to Prevent Employee Attrition
Read how to boost employee retention by 300% with employee onboarding automation
Written by : Fauzul Fahmi & Kezia Nadira
| 2023-01-18T00:00:00 |
2023/01/18
|
https://gleematic.com/hr-automation-how-ai-is-changing-the-game/
|
[
{
"date": "2023/02/08",
"position": 86,
"query": "artificial intelligence hiring"
}
] |
Artificial Intelligence: opportunities and challenges
|
Artificial Intelligence: opportunities and challenges
|
https://knowledge.epr.equass.be
|
[] |
AI is playing an increasingly important role in the recruitment and hiring process as well, thanks to its ability to analyse huge data sets about different ...
|
Artificial Intelligence: opportunities and challenges
Opportunities
AI offers many opportunities for our economy and society. In the economy and the world of work, AI can enrich many professions and redefine workers’ tasks in an easier way, improving efficiency in terms of speed and quality. AI doesn’t only contribute to efficient task management, but also to the promotion of healthy habits in the workplace. AI-powered sensors, wristbands and digital questionnaires can be used to collect large quantities of data about workers’ stress, physical and psychological strain and to suggest employees actions to improve their well-being at work. Such tools can help prevent health issues or disabilities and manage existing ones, therefore assisting people with disabilities in their professional activities.
AI is playing an increasingly important role in the recruitment and hiring process as well, thanks to its ability to analyse huge data sets about different profiles and identify the candidates with the right characteristics and skills. For example, AI-based recruitment tools help companies to advertise their job offers among targeted profiles that match specific requirements set by the employers, therefore increasing the number of qualified applications. Furthermore, AI can help hirers to save time in the screening of CVs by quickly processing them, always while looking for specific requirements. AI is also improving the experience of jobseekers and candidates during the selection process, for instance by offering them ads on jobs that best suit their skills, interests and career goals, or by providing them with assistance through AI chatbots or feedback after applying for a job.
When it comes to the impact of AI on our society, this technology has a great potential to fill the gap of social inequality, especially between the mainstream population and vulnerable groups like people with disabilities, by offering them more opportunities in their daily life and promoting their independence. In this context, AI can offer a great support to social services providers by facilitating the communication with users, helping them to better understand their needs and offer care solutions that truly promote their social inclusion and autonomy.
AI can be applied in a wide range of Assistive Technology (AT) to support people with disabilities in their daily lives. Some examples include:
Human-Machine Interaction: Brain-machine interfaces (BCI) encode signals emitted by the brain and help people with disabilities to interact with an environment, control objects and interact with intelligent machines like tablets, robots, but also smart vehicles;
Brain-machine interfaces (BCI) encode signals emitted by the brain and help people with disabilities to interact with an environment, control objects and interact with intelligent machines like tablets, robots, but also smart vehicles; Robots: robots that use AI technology to manipulate objects and increase perception can provide guidance for blind people, people with intellectual disabilities and those who need help for orientation in spaces unknown to them (e.g. in hospitals or airports). Technological innovation is also leading to the diffusion of the so-called “Care Robots”, social robots which thanks to AI can reproduce human actions safely and efficiently and assist persons with cognitive deficits or reduced mobility in multiple daily actions, keeping them company by becoming telephones or TVs, and facilitating the work of social services workers;
robots that use AI technology to manipulate objects and increase perception can provide guidance for blind people, people with intellectual disabilities and those who need help for orientation in spaces unknown to them (e.g. in hospitals or airports). Technological innovation is also leading to the diffusion of the so-called “Care Robots”, social robots which thanks to AI can reproduce human actions safely and efficiently and assist persons with cognitive deficits or reduced mobility in multiple daily actions, keeping them company by becoming telephones or TVs, and facilitating the work of social services workers; Robotic technologies: prostheses, wearables, exoskeletons enhance self-control in rehabilitation processes, supported by the monitoring of medical professionals;
prostheses, wearables, exoskeletons enhance self-control in rehabilitation processes, supported by the monitoring of medical professionals; AI technologies such as natural language processing, speech-to-text and voice recognition applications: these technologies can assist people with speech impairments to be understood by normalising impaired speech (an example is Google’s Parrotron). Similarly, people with hearing disabilities can benefit from AI-based applications that through computer vision translate sign language into speech or perform lip-reading thanks to specific algorithms (like Google’s DeepMind). People with limited vision can be supported by AI-based computer vision apps which are able to describe the environment, objects and people, as well as to read texts from newspapers, smartphones and so on (like Microsoft’s Seeing AI).
AI can help significantly in the education and training of people with disabilities, especially by offering personalised learning content according to data on people’s learning style and past behaviours. AIpowered training programs can adapt more flexibly to suit the needs of learners, to identify their weaknesses and recommend them further training. Social services providers that work on training opportunities for people with disabilities can benefit a lot from these programmes, because their level of adaptation can increase accessibility of education and training for people with disabilities. According to the learner’s disability, for instance, these programmes can offer lessons in the form of video tutorials with or without automatic transcriptions, or in the form of texts automatically read. An example of AI-powered learning application for people with disabilities is I-Stem, which analyses and converts into formats accessible to persons with vision impairments or learning disabilities documents or images with maths, tables or columns, promoting their education in STEM subjects.
Challenges
The radical changes brought about by rapid technological progress and the diffusion of AI in many sectors offer opportunities, but also pose some major challenges, outlined below.
Education. The overall digital transition is increasing the demand for digital skills in the labour market, which will soon become indispensable to access to future jobs. Considering the complexity of AI technology and the importance to harness it responsibly, there is an urgent need to educate all levels of society on AI uses and applications, starting from young students in compulsory education with 6 programs on computational thinking, algorithm solving etc., and moving on to VET and professional training for adults. Education on AI is fundamental to fully harness AI’s potential, since only by understanding its functioning and the challenges it poses can we use it responsibly and adequately. For education systems to adapt to this demand, heavy investment from governments is needed. Furthermore, it is important to ensure that such programmes are accessible also from people with disabilities. To do so, it can be useful to use some of the inclusive learning tools that AI already offers and that were mentioned above.
Professional training and skills. The need to train people on AI applies also to professionals and employees, since the gradual integration of AI technology into the organisation of work and the management of tasks will require them to reskill and upskill in order to fully harness it. This is a big challenge especially in the social service sector, where the lack of specific ICT training of staff is often bigger compared to other sectors and requires significant investment. Adequate professional training must include people with disabilities, who are often excluded from the labour market and have less training opportunities. Given the rapid transformations in the labour market, keeping these groups updated with technological developments is crucial to improve their chance to access employment opportunities. In this regard, the sharing of information and best practices among service providers and networks such as EPR is extremely useful.
Lack of regulations on accountability. AI also poses key questions concerning ethics and accountability, as it is still difficult to determine whether possible mistakes are the fault of the machine or the humans who designed it. This lack of clear accountability is one of the reasons why citizens might distrust the use of AI and find it opaque. This calls for the development of standards and regulations that ensure that AI products and services are used responsibly and with a transparent decision-making process. At the EU level, the Commission’s Proposal for a Regulation on AI addresses namely this current lack of regulations.
Bias in recruitment. The need for regulations and minimum professional standards on ethics and accountability also relates to one of the major challenges posed by AI, that is the risk of bias in recruitment. AI tools are based on human programmers, their ideas and assumptions, and might therefore pick up human errors and bias. Such bias create an issue of accountability and can reinforce discrimination due to age, ethnicity, disability etc. Homogeneous systems might in fact favour people with similar characteristics to those already employed and exclude groups that are not equally represented in data sets. People with disabilities might therefore be excluded from the labour market and be left behind by these systems, which would turn into another barrier rather than an advantage. Social services providers must therefore work to raise awareness among employers using AI in recruitment about the need of people with disabilities to have a more personalised approach.
Accessibility and inclusive design. The challenge of inclusion requires the promotion of standards of accessibility of AI tools and a human-centred approach to their development. If AI is not transparent enough and users cannot understand why the tool came up with some answers instead of others, it might become a new barrier for many, including people with disabilities. Furthermore, efforts must be made to ensure that people with disabilities can make informed decisions when it comes to using AI and AT products and services. For this reason, awareness about the topic of accessibility must be raised among IT professionals and engineers who should adopt an inclusive design for AI tools and services, so that these solutions truly consider the needs of everyone and improve the experience of all users. Challenges are an additional opportunity for development that can highlight the elements of provision, legislation, communication, cooperation and so forth that should or could be improved.
| 2023-02-08T00:00:00 |
https://knowledge.epr.equass.be/article/525-artificial-intelligence-opportunities-and-challenges
|
[
{
"date": "2023/02/08",
"position": 90,
"query": "artificial intelligence hiring"
}
] |
|
Unilever's Practice on AI-based Recruitment
|
Unilever‘s Practice on AI-based Recruitment
|
https://drpress.org
|
[
"Qirui Hu"
] |
This article uses the case analysis method to discuss Unilever's application of AI in the recruitment and selection process.
|
Busuioc, M. Accountable artificial intelligence: Holding algorithms to account. Public Administration Review, 2021, 81(5), 825–836.
Schlegelmilch, BB. Why business schools need rad- ical innovations: Drivers and development trajectories. Journal of Marketing Education, 2020, 42(2), 93–107.
Cappelli, P., Tambe, P., & Yakubovich, V. Can data science change human resources? In J. Canals & F. Heukamp (Eds.), The future of management in an AI world: Redefining purpose and strategy in the fourth industrial revolution. Springer International Publishing, 2020, 93–115.
Walkowiak, E. Digitalization and inclusiveness of HRM practices: The example of neurodiversity initiatives. Human Resource Management Journal, 2023,1– 21.
Nkomo, S. M., Bell, M. P., Roberts, L. M., Joshi, A., Thatcher, S. M. B. Diversity at a critical juncture: New theories for a complex phenomenon. Academy of Management Review, 2019, 44(3), 498–517.
Brouer, R., Badawy, R. and Stefanone, M. "Social media and recruitment: examining (counter) productive diversity messages", Organization Management Journal, 2022, 19 (1), 34-43.
Thomas, D. A. Diversity as strategy. Harvard Business Review, 2004, 82(9), 98-98.
Polanyi, M. The tacit dimension. University of Chigago Press, 2009.
HireVue, Unilever + HireVue: Unilever finds top talent faster with HireVue assessments, 2023. Retrieved on March 29, 2023. Retrieved from: https://www.hirevue.com/case-studies/global-talent-acquisition-unilever-case-study.
Young, J., Foot, K. Corporate E-cruiting: The construction of work in fortune 500 recruiting websites. Journal of Computer-Mediated Communication, 2005, 11(1), 44-71.
Brad A. M. Johnson, Jerrell D. Coggburn, Jared J. Llorens. Artificial Intelligence and Public Human Resource Management: Questions for Research and Practice. Public Personnel Management, 2022.
Windscheid, L., Bowes-Sperry, L., Kidder, D., Cheung, H., Morner, M., Lievens, F.. Actions speak louder than words: Outsiders’ perceptions of diversity mixed messages. Journal of Applied Psychology, 2016, 101(9), 1329-1341.
Guo, F., Gallagher, C. M., Sun, T., Tavoosi, S., & Min, H. Smarter people analytics with organizational text data: Demonstrations using classic and advanced NLP models. Human Resource Management Journal, 2021, 1– 16.
Speer, A. B. Quantifying with words: An investigation of the validity of narrative-derived performance scores. Personnel Psychology, 2018, 71, 299– 333.
McColl, R, Michelotti, M. Sorry, could you repeat the question? Exploring video-interview recruitment practice in HRM. Hum Resour Manag, 2019; 29: 637–656.
Mirowska, A., Mesnet, L. Preferring the devil you know: Potential applicant reactions to artificial intelligence evalua- tion of interviews. Human Resource Management Journal, 2021, 32(2), 1748–8583.
Michelotti, M., McColl, R., Puncheva-Michelotti, P., Clarke, R., McNamara, T. The effects of medium and sequence on personality, 2021.
Schwab, K. The fourth industrial revolution. Currency, 2017.
American Psychiatric Association Foundation. Workplace mental health—employee mental health and well-being during and beyond COVID-19. 2020. Retrieved on March 29, 2023. Retrieved from: http://www.workplacementalhealth.org/Employer-Resources/Employee-Mental-Health-Well-being-During-Beyon.
| 2023-02-08T00:00:00 |
https://drpress.org/ojs/index.php/HBEM/article/view/10565
|
[
{
"date": "2023/02/08",
"position": 96,
"query": "artificial intelligence hiring"
}
] |
|
Tech layoffs have disproportionately affected women. ...
|
The recent tech layoffs have disproportionately affected women. Here's why.
|
https://www.msnbc.com
|
[
"Daniela Pierre-Bravo"
] |
Research conducted by Eighfold AI found that women in tech were 65 percent more likely to be laid off than men. And as FastCompany pointed out, approximately 45 ...
|
In August of 2022, Lola Adewuya moved from Vancouver, Washington to the Bay Area to be closer to Google’s headquarters. She had worked in marketing for the tech company for two-and-a-half years and was excited to finally work in-person with many of her colleagues.
But five months later, on Jan. 20 of this year, the seemingly unexpected happened. Adewuya, 24, found out she was being laid off, alongside three other members of her seven-person team.
“I had a full-on panic attack, I'm not gonna lie,” Adewuya told Know Your Value. “After I read the email, I called my mom and just sobbed because it came as a complete surprise…"
Adewuya is one of 12,000 employees who were laid off by the tech giant’s parent company, Alphabet, this year. Other tech companies have made similar moves, including at Microsoft and Salesforce. Paypal and Groupon also recently announced that they’re planning for employee cuts. And this week, Dell slashed 5 percent of its global employee base, or 6,650 jobs.
For women working in tech, like Adewuya, these layoff numbers exacerbate an existing problem. Not only are women underrepresented in the industry (they make up around 26 percent) but they’re also disproportionally affected by the job cuts.
Research conducted by Eighfold AI found that women in tech were 65 percent more likely to be laid off than men.
And as FastCompany pointed out, approximately 45 percent of those who were laid off in the recent round of tech job cuts were women. That’s according to Layoffs.FYI, which monitors the tech industry. And although that’s less than half, that number is quite significant because women make up less than a third of tech industry workers.
Workforce experts said one reason why women in tech are being disproportionately laid off is because there are more women in roles that are often the first to be cut. That includes customer-facing roles like marketing, customer service, human resources and recruitment. There are also fewer women in more technical roles that are deemed essential, like engineering and coding.
Experts also said women and minorities are more likely to represent newer hires in tech, partially because greater remote work opportunities. But it’s also left them more susceptible to layoffs. “Many of these people who were hired recently, they are the last in. And quite often because they were the last in, they built fewer relationships among their colleagues and with their managers. So, they're also the first out.” Bhaskar Chakravorti, dean of global business at The Fletcher School at Tufts University, explained. “Because many of them were remote, they didn't have the opportunity to set up those personal relationships that often develops in the corridors, in the offices and around the water coolers.”
Sandra Lopez was recently laid off from her Chief Marketing Officer role at Microsoft Advertising after a year working at the company. Lopez said the news didn’t take her by surprise because “as an executive, you're pretty tuned [into] the business climate.” But she said she is worried about the long-term effects of the already low representation of women of color, like her, in tech.
Sandra Lopez said she was laid off from a Chief Marketing Officer role at Microsoft Advertising. Adam Bacher
“We represent the seventh largest economy in the world. We're the largest growing minority in the United States. It's not only about efficiency in this moment in time. It's also about making sure you have the right people to prepare you for tomorrow and to make sure that what you're developing will be relevant for your consumer audience,” Lopez said.
Chakravorti noted that the layoffs happening to women in tech now may impact the future of tech and artificial intelligence. “It is really important to have an AI workforce that is representative of the wider population,” he said. “If it is very skewed in one direction, whether it's gender or race, it introduces a degree of bias into the algorithm … The fact that women are being disproportionately let go also has an impact on the quality of the AI product that many of these companies are working on and developing.”
Despite the layoffs, the tech industry added nearly 260,000 jobs last year. The last time the sector saw numbers that high was in 2000. And although it remains to be seen if those hiring numbers will continue into this year (and how many of them will be filled by women), a ZipRecruiter survey from late October of last year, found that almost 80 percent of laid off tech workers found new jobs within three months.
Marisa Lascher, an expert in positive psychology and a human resource executive, shared a few steps on how to find resiliency after a layoff. She stressed the importance of “feeling,” “dealing” and “distancing.”
First, let yourself feel. “Welcome your emotions and get them out in productive ways like exercising, journaling, or talking to a loved one. Write yourself a compassionate letter about the situation: What would you say to a close friend going through your situation?”
In the deal phase, Lascher recommended getting focused by writing objectives for your job search. “Have clear results, measurable outcomes and update them as necessary. You are your own manager now – you have freedom to do what you want. Find an accountability partner who motivates and inspires you.”
And finally, distance yourself from your situation. Pretend you’re watching what’s happening in your life from far away to gain perspective and objectivity, she advised.
After getting laid off, Adewuya said she is taking this time to pivot and focus on her side gig – a design studio called The Brand Doula – and turning it into a full-time entrepreneurship venture. “I've never been more happy to have had this going on, to have a side hustle. To not put all of my eggs in this basket, no matter how secure it might feel,” she said.
| 2023-02-09T00:00:00 |
2023/02/09
|
https://www.msnbc.com/know-your-value/business-culture/tech-layoffs-have-disproportionately-affected-women-here-s-why-n1302865
|
[
{
"date": "2023/02/08",
"position": 46,
"query": "artificial intelligence layoffs"
}
] |
Alphabet's Bard AI Misfires in Debut, Shares Swoon
|
Alphabet's Bard AI Misfires in Debut, Shares Swoon
|
https://www.investopedia.com
|
[
"Igor Greenwald",
"Igor Is An Experienced Finance Journalist. He Has Covered U.S.",
"Global Financial Markets",
"Business",
"Economics As An Editor",
"Columnist For More Than Two Decades.",
"Learn About Our",
"Editorial Policies"
] |
An error by Google AI chatbot cost parent Alphabet almost $100B in market cap. The AI rush continues as Microsoft rolled out its AI-assisted search and ...
|
An early skirmish in the race for artificial intelligence supremacy had Alphabet (GOOG, GOOGL) shares down about 8% in afternoon trading Wednesday, wiping out almost $100 billion in market cap after a demonstration of its AI-powered chat interface Bard showed off the technology's flaws of making plausible-sounding misstatements.
Key Takeaways Alphabet shares fell 8% Wednesday after the company and rival Microsoft unveiled AI-assisted search features this week.
Alphabet's AI chatbot Bard made a factual error in its first public demonstration.
Microsoft recently invested an additional $10 billion in OpenAI, whose popular ChatGPT makes mistakes as well.
Artificial intelligence technology has been called "the next big thing" and related stocks have posted big gains recently.
Alphabet CEO Sundar Pichai unveiled Bard late Monday, calling it "the most profound technology we're working on today."
The demonstration showed the chatbot's answer to a question about new James Webb Space Telescope (JWST) discoveries that one could discuss with a 9-year old. Bard credited JWST with taking "the very first pictures of a planet outside of our solar system." By Tuesday, Twitter users were noting that the first exoplanet was imaged by the European Southern Observatory in Chile in 2004.
YCharts
OpenAI's popular AI chatbot ChatGPT, which fueled the recent conversation around AI, has also told a whopper or two in its time. The large language models both ChatGPT and Bard deploy to sound convincingly human are geared to showcase fluency, not factual or logical rigor.
However, that hasn't stopped tech mega caps from tripping over each other to highlight their grasp of the technology. A day after Bard's launch, Microsoft (MSFT) announced it would augment its Bing search engine with AI features from its partner OpenAI.Coming off a costly earnings miss, Intel (INTC) discussed "unlocking the potential of generative AI" in an editorial published Wednesday. Microsoft recently announced a $10 billion investment in OpenAI, making Microsoft's Azure OpenAI's exclusive cloud computing provider.
But Alphabet potentially has more at stake in the race to develop a technology capable of replacing online searches with reliable and relevant answers. Google search advertising is the company's primary moneymaker, while Bing is far from raking in big bucks for Microsoft.
The AI boom could benefit chip maker Nvidia (NVDA) in the long term, Wedbush analysts said in a research note Wednesday. "We see the inclusion of additional AI capabilities into search as driving incremental longer-term demand for hardware," they wrote. "Most notably there will need to be incremental accelerators to meet increased AI requirements for search (a result that is a significant longer-term positive for NVDA which continues to dominate the AI market), but also incremental storage, memory, etc. will be required to support the uptick in AI needs."
In the meantime, visitors to the ChatGPT site Wednesday were intermittently informed that "ChatGPT is at capacity right now."
| 2023-02-08T00:00:00 |
https://www.investopedia.com/alphabet-chatbot-tanks-stock-microsoft-launches-own-ai-7107129
|
[
{
"date": "2023/02/08",
"position": 98,
"query": "artificial intelligence layoffs"
}
] |
|
AI in Recruitment - Everything you need to know - Jobylon
|
Everything you need to know
|
https://www.jobylon.com
|
[] |
AI for recruitment can assist in sourcing and screening candidates, analyzing resumes and job applications, conducting pre-employment assessments, and even ...
|
Artificial intelligence (AI) is revolutionizing the world of work. So, it is no surprise that this transformation extends to HR and talent acquisition (TA) professions and activities. While adoption is high across various functions and job roles, HR professionals report that AI use is a growing priority and express optimism about its potential usefulness for day-to-day activities. Organizations are seeing results from AI adoption and how it can be leveraged to improve their recruitment efforts. With AI’s estimated contribution to the global economy to be nearly $16 trillion by 2030, its role in recruitment will only continue to grow.
Recruitment includes many resource and time-intensive activities that can be fraught with challenges and unexpected delays. From sourcing and screening candidates to conducting interviews and assessing talent, recruiters need to navigate a wide range of processes to find the right fit for their company’s needs. The rise of AI means that many of these tasks can be simplified, saving recruiters, talent acquisition specialists, and hiring managers time and resources. In this article, we explore how AI is transforming the recruitment process and the benefits it brings to employers.
What is AI for recruitment?
AI for recruitment refers to the application of artificial intelligence technology in the hiring process to streamline and automate various aspects of recruitment. AI can help recruitment teams make quicker and better hiring decisions. AI for recruitment can assist in sourcing and screening candidates, analyzing resumes and job applications, conducting pre-employment assessments, and even predicting candidate success and cultural fit.
By leveraging AI, recruiters can save time and resources, improve the quality of candidate matches, reduce bias, and make data-driven decisions. AI for recruitment holds the potential to revolutionize the hiring landscape by increasing efficiency, accuracy, and overall effectiveness in identifying and attracting the right talent for organizations.
How does AI benefit recruitment?
With AI-driven technology, recruitment teams can offload repetitive and manual tasks and focus their time and efforts where their skills are most needed.
Here are 4 reasons why every recruiter and TA professional should stay updated about AI in recruitment:
1. Maximize recruitment efficiency
Recruitment is typically a lengthy process that involves a lot of manual work. The average recruiter spends up to 30 hours a week on administrative tasks like sourcing candidates, screening resumes, scheduling interviews, and coordinating with other members of hiring teams.
Rather than spending resources on these admin-intensive activities, AI-based solutions can source through thousands of applications in an instant and identify qualified candidates. This can help HR and TA teams reduce the amount of time they spend on administrative work so they can focus on strategic tasks that will actually help deliver results for their organization.
2. Overcome recruitment bias
Human biases can often creep into the recruitment process and influence decisions in ways that are not aligned with corporate values and priorities. Almost 50% of HR managers admit to being affected by unconscious bias when selecting candidates.
This can result not only in poor hiring decisions but can also work against an organization’s efforts to build a diverse workforce. When used correctly, AI can counteract these biases and eliminate subjectivity in the hiring process. AI is able to screen candidates objectively based on factors such as qualifications and experience without relying on subjective factors like age, gender, and race.
3. Enhanced candidate experience
An inefficient recruitment process and impersonal approach can be a major turnoff for job applicants and lead to a poor candidate experience. In fact, a survey revealed that 52% of job seekers report declining a job offer due to a poor recruitment experience.
Not only can this discourage candidates from applying again in the future, but it can also dissuade those in their networks, as a bad experience travels fast in today’s highly digital and social world.
AI-enabled recruitment tools can help mitigate this problem by making the entire recruitment process more engaging and personalized, which in turns improves candidate experience and attracts more qualified candidates.
4. Improve the quality of hires
Employees are the lifeblood of a business, and one bad hire can have a serious impact on the company’s productivity and bottom line. According to the United States Department of Labor, a poor hire can cost a company 30% of the employee's first-year salary. The cost is estimated to be greater by some HR agencies, ranging from $240,000 to $850,000 per employee. This is where AI can prove to be beneficial. When used alongside traditional methods, AI-powered recruiting solutions can quickly assess candidates based on data and insights that can help managers make more informed decisions.
5. Slash time to hire
Saving time at any stage of the recruitment process directly impacts how long it takes to make a hire. The traditional linear approach of hiring–source, screen, interview, assess, offer, hire–is being disrupted by AI as these processes can be integrated or happen in parallel. For example, while recruiters conduct interviews, AI can simultaneously source and screen new candidates, reducing the overall hiring timeline.
While quality of hire remains a top priority, AI can help talent teams find quality candidates faster while reducing the manual effort required to find, communicate, secure, and onboard top talent.
How to use AI in recruitment today
AI has already proven to be a smart and cost-effective way of speeding up the recruitment process while also improving the quality of hires. Below is a detailed look at how AI can benefit various aspects of the talent acquisition process.
1. Candidate sourcing
AI-based sourcing solutions make it easier for recruiters to locate and connect with relevant talent quickly. These tools use algorithms and machine learning to search job boards, internal databases, and social media platforms, to source the most relevant candidates for a particular role.
There are a number of AI-based sourcing tools available on the market, each with its own unique features and capabilities. For example, some tools focus on maximizing recruitment marketing efforts and connecting with candidates in real time, while others have an AI chatbot that interacts with candidates to find the best role fit and give them information on how to apply. These tools offer a wide range of benefits to recruiters, including faster candidate sourcing, improved accuracy and efficiency, and better team collaboration.
2. Candidate screening
Screening is a critical step in the hiring process. However, this step can also be especially time-consuming when dealing with large volumes of applications. This is where AI screening tools come into play. By utilizing AI technology, these tools can quickly extract important information from job applications that can be useful for hiring decisions and efficiently bring the best candidates to the forefront. Chatbots and conversational AI tools can also be used in the initial screening by automatically filtering candidates based on basic requirements such as age, legal right to work, driving capabilities, etc.
The methods used by AI screening systems vary, ranging from resume parsing to behavioral and skill evaluations. For instance, the AI screening system may identify red flags indicating incompatible personalities or behavior patterns that may not be a good fit for a particular role. These insights can then be used by the recruiter in the selection process to narrow down the candidate pool and focus on those with higher potential.
3. Talent assessment
AI-powered talent assessment tools are increasingly being used by companies to measure candidate competency and personality traits. These tools can offer a more comprehensive and efficient way to assess candidates by incorporating gamification, behavioral assessments, and skill testing. The data generated from these tools are analyzed by AI algorithms to provide an in-depth report on a candidate's strengths, weaknesses, and personality traits. This not only saves time and resources for the organizations but also provides a better experience for the candidates by allowing them to showcase their abilities in an engaging and interactive way.
Moreover, most of these tools can be customized according to the needs of a particular organization and can be integrated with existing systems, including your ATS, to ensure a seamless workflow.
2025 Recruitment Trends How to navigate recruitment in 2025. Featuring tips and insights from talent acquisition and HR experts.
4. Candidate interviews
Interviews are a critical step of the hiring process. AI-enabled platforms can conduct pre-screening interviews via video calls or text-based interactions, recording and analyzing responses to help identify the most suited candidates.
AI can also assist with transcribing and summarizing interviews, making it easier to share insights among hiring teams. By providing exact transcripts, AI helps teams make more informed and less biased hiring decisions, reducing reliance on gut feelings or memory recall.
Additionally, AI simplifies scheduling—a tedious but essential task. Coordinating the schedules of candidates with your hiring teams can be offloaded to AI tools that will do the simple, but laborious work for you.
5. Offer and onboarding
When it comes to offers and onboarding, creating a positive and engaging experience is key to successfully converting candidates into new hires and setting them up for a strong start. With AI-based tools it has become easier for HR teams to create an engaging and personalized onboarding experience for new employees. From introducing new hires to the organization and its culture to helping them navigate their first days on the job, these solutions streamline the onboarding process and ensure a smooth and memorable experience for every new hire.
The use of machine learning and AI technology enables these platforms to understand the unique needs of each organization and provide a tailored onboarding experience while also scaling the process to accommodate large numbers of new hires. Ultimately, by prioritizing employee engagement and creating a positive first impression, organizations can set the stage for a successful and productive long-term relationship with their new hires.
Do you want to make your recruitment process more data-driven and efficient? Take a look at our recruitment platform! You can book a free demo to have the full experience of the tool and ask questions you might have.
| 2023-02-09T00:00:00 |
https://www.jobylon.com/blog/how-ai-is-transforming-the-world-of-recruitment
|
[
{
"date": "2023/02/09",
"position": 36,
"query": "artificial intelligence hiring"
},
{
"date": "2023/02/09",
"position": 67,
"query": "AI hiring"
},
{
"date": "2023/02/09",
"position": 9,
"query": "workplace AI adoption"
},
{
"date": "2023/02/09",
"position": 33,
"query": "AI labor market trends"
},
{
"date": "2023/02/09",
"position": 18,
"query": "AI workers"
},
{
"date": "2023/02/09",
"position": 61,
"query": "AI hiring"
},
{
"date": "2023/02/09",
"position": 8,
"query": "artificial intelligence employers"
},
{
"date": "2023/02/09",
"position": 1,
"query": "artificial intelligence hiring"
},
{
"date": "2023/02/09",
"position": 51,
"query": "AI hiring"
},
{
"date": "2023/02/09",
"position": 34,
"query": "artificial intelligence hiring"
},
{
"date": "2023/02/09",
"position": 30,
"query": "artificial intelligence hiring"
},
{
"date": "2023/02/09",
"position": 64,
"query": "AI hiring"
},
{
"date": "2023/02/09",
"position": 72,
"query": "AI hiring"
},
{
"date": "2023/02/09",
"position": 33,
"query": "artificial intelligence hiring"
},
{
"date": "2023/02/09",
"position": 62,
"query": "AI hiring"
},
{
"date": "2023/02/09",
"position": 65,
"query": "AI hiring"
},
{
"date": "2023/02/09",
"position": 32,
"query": "artificial intelligence hiring"
},
{
"date": "2023/02/09",
"position": 34,
"query": "artificial intelligence hiring"
},
{
"date": "2023/02/09",
"position": 33,
"query": "artificial intelligence hiring"
},
{
"date": "2023/02/09",
"position": 65,
"query": "AI hiring"
},
{
"date": "2023/02/09",
"position": 65,
"query": "AI hiring"
},
{
"date": "2023/02/09",
"position": 34,
"query": "artificial intelligence hiring"
},
{
"date": "2023/02/09",
"position": 37,
"query": "artificial intelligence hiring"
},
{
"date": "2023/02/09",
"position": 60,
"query": "AI hiring"
},
{
"date": "2023/02/09",
"position": 34,
"query": "artificial intelligence hiring"
},
{
"date": "2023/02/09",
"position": 31,
"query": "AI hiring"
},
{
"date": "2023/02/09",
"position": 57,
"query": "AI hiring"
},
{
"date": "2023/02/09",
"position": 55,
"query": "AI hiring"
},
{
"date": "2023/02/09",
"position": 33,
"query": "artificial intelligence hiring"
}
] |
|
The benefits (and the downsides ) of AI for the recruitment ...
|
The benefits (and the downsides ) of AI for the recruitment sector
|
https://www.sonovate.com
|
[] |
AI has the potential to impact job creation both positively and negatively. On one hand, it can automate certain tasks, which may lead to job losses in certain ...
|
Contents:
How can AI help in recruitment?
When should a recruitment business use AI and when should it rely on humans?
How can AI reduce bias and support diversity and inclusion in the recruitment process?
What are the potential pitfalls of using AI in recruitment?
Should recruitment businesses develop their own AI or get it from a specialist vendor?
What should recruitment businesses look for when looking for an AI solution?
If developed in-house, what should recruitment businesses do when training their AI?
Will AI impact the recruitment industry by causing job losses?
What is the guidance around the use of Artificial Intelligence?
Artificial Intelligence (AI) has seen significant growth and development in recent years. AI is being widely adopted across a variety of industries and is having a profound impact on many aspects of our lives. AI technologies, such as machine learning and natural language processing, have improved greatly and are now being used in areas like healthcare, finance, and customer service. They are developed to tackle complex tasks and make human lives easier and more efficient.
In the UK, the DCMS (Department for Digital, Culture, Media & Sport) appointed EY to conduct an evidence analysis and primary market research to assess the extent of data foundations and AI adoption. The research findings “Data foundations and AI adoption in the UK private and third sectors” were published in August 2021 and the overwhelming response from participants suggested that data is deemed important to the success and growth of organisations across the private and third sector.
The research found that adoption is significantly higher in the UK private sector, with 70% of private-sector organisations planning or already using AI, which compares with 42% in the third sector. Within the UK private sector, 90% of large organisations have planned or already adopted AI, compared with 48% of SMEs. From an industry perspective, organisations operating in Finance and Technology, Media and Telecom (TMT) report the highest levels of adoption.
In the recruitment industry, the rise of AI has also been substantial. AI technologies are being increasingly adopted to streamline and optimize various aspects of the recruitment process. AI algorithms can be used to automate many tasks, some of which are described below. This has resulted in increased efficiency and productivity for recruiters, as well as a better candidate experience. AI has also been able to tackle issues such as unconscious bias and has the potential to enhance diversity in the hiring process.
As with any transformation, AI adoption also has its hazards. There are a variety of concerns regarding this technology, ranging from job displacement to ethical concerns, so guidelines around its use have started to be developed. This article looks at the growing use of AI in recruitment, how the industry can benefit from it and what it can do to avoid potential pitfalls. We’ll also touch on guidelines, in the UK and other parts of the world, around it.
How can AI help in recruitment?
When trained and used correctly, AI can increase efficiency, reduce manual work, and provide valuable insights and predictions, allowing recruiters to make data-driven decisions to grow their business and improve the candidate experience. Some of the uses of AI in recruitment are:
Automated Resume Screening: AI can quickly sort through large amounts of resumes, identifying the most relevant candidates based on specific job requirements, saving recruiters time and effort.
Predictive Analytics: AI can analyse data on job market trends, salary benchmarks, and other factors to make predictions on talent supply and demand, allowing recruitment companies to make better decisions on where to focus their efforts.
Predictive hiring: AI algorithms can analyse data from past hiring practices to identify patterns and make predictions about which candidates are most likely to be successful.
Personalised job matching: AI can match candidates with job opportunities based on their skills, experience, and preferences.
Chatbots: AI-powered chatbots can handle repetitive tasks such as answering frequently asked questions and scheduling interviews, freeing up recruiters to focus on more strategic tasks.
Video Interviewing: AI can provide a more objective and consistent evaluation of candidates through the use of video interviewing, reducing the risk of human bias and improving the accuracy of the selection process.
When should a recruitment business use AI and when should it rely on humans?
The predominant view from thought leaders and industry experts is that recruiters should use a combination of AI and human involvement in the recruitment process to leverage the strengths of both. AI can be used to handle repetitive and simple tasks, while human recruiters can provide the critical thinking, empathy, and judgement necessary to make well-informed hiring decisions.
When deciding whether to use AI or rely on humans in the recruitment process, recruiters should consider the following:
Complexity of the task: AI can handle repetitive and simple tasks quickly and accurately, while human recruiters are better suited to handle more complex and nuanced tasks that require critical thinking and judgement.
Candidate experience: While AI can automate certain aspects of the recruitment process, human recruiters are often better equipped to provide a personalized and empathetic candidate experience.
Bias: AI algorithms can minimise unconscious bias in the recruitment process, but they can also perpetuate existing biases in the data they are trained on. Human recruiters have the ability to recognise and counteract bias in the recruitment process.
Data privacy: AI technologies can handle and process large amounts of candidate data, but there are concerns about the privacy and security of this data. Human recruiters are better equipped to ensure the appropriate handling of sensitive candidate information.
How can AI reduce bias and support diversity and inclusion in the recruitment process?
AI can help reduce bias and support diversity in the recruitment process in several ways:
Resume screening: AI algorithms can be trained to screen resumes objectively and eliminate human biases in the selection process. By removing names, addresses, and other personal information from resumes, AI algorithms can help to prevent unconscious bias.
Predictive hiring: AI systems can analyse vast amounts of data to identify patterns and make predictions about which candidates are likely to be successful in a particular role. By using a data-driven approach, AI can reduce the impact of human biases in the hiring process.
Skill-based matching: AI systems can match candidates to job openings based on their skills and qualifications, rather than demographic information or other biases.
Diversity monitoring: AI systems can analyse recruitment data to identify areas where bias may be present, such as underrepresented groups being less likely to be invited to interview or offered a job. Recruiters can then take steps to address these biases and promote diversity in the recruitment process.
However, it is important to note that AI algorithms can only be as unbiased as the data they are trained on. Therefore, organisations who either purchase an AI system, or develop it in house should ensure that their algorithms are fit for purpose, that their AI is trained correctly and that their recruitment data is diverse and free from bias.
What are the potential pitfalls of using AI in recruitment?
While AI has the potential to improve recruitment processes, it is essential to be aware of possible downsides and to take appropriate measures to mitigate them.
Such risks could include:
Bias: AI algorithms may perpetuate existing biases in the recruitment process, such as gender, race, or age bias. As mentioned above, it is critical to ensure that the data used to train the AI is diverse and unbiased and that the AI is regularly tested for fairness.
Lack of transparency: AI-driven recruitment processes can sometimes be opaque, making it difficult for candidates and recruiters to understand how decisions are being made. This can result in a lack of trust and may negatively impact the candidate experience.
Ethical concerns: AI raises a number of ethical questions, including issues around privacy, accountability, and control.
Privacy concerns: The use of AI in recruitment requires access to personal data, which can raise privacy concerns. It is essential to ensure that the AI solution is secure and that the vendor has appropriate data protection measures in place.
Unreliability: AI algorithms are only as good as the data they are trained on. If the data used for training is inaccurate or outdated, the AI’s predictions may be unreliable.
Displacement of human recruiters: AI-driven recruitment may result in the displacement of human recruiters, potentially leading to job losses and causing negative social and economic impacts.
Technical issues: AI algorithms are complex and can be prone to technical issues, such as bugs or system failures. It is important to ensure that the AI solution has robust backup and recovery systems in place.
Security risks: AI systems can be vulnerable to cyber attacks, which can have serious consequences, particularly in critical systems such as healthcare, finance, and transportation.
Unintended consequences: The deployment of AI systems can have unexpected and sometimes undesirable consequences, particularly when they are used in complex real-world settings.
Dependence on algorithms: Relying too heavily on AI can result in a loss of critical thinking and decision-making skills, as well as a reduced ability to understand and interpret the world around us.
From academics to businesses, Chat GPT’s meteoric rise is causing concern across all fields. The misuse of AI and automation tools in recruitment has become a growing concern as these tools can be used to manipulate and fabricate data to give an unrealistic view of a candidate’s qualifications and experience, or their cultural fit with the hiring organisation. Therefore, it is important for recruiters to be aware of such trends and be extra vigilant when reviewing CVs to ensure that they are receiving genuine applications from qualified candidates.
Should recruitment businesses develop their own AI or get it from a specialist vendor?
Both developing an AI in-house and obtaining it from a vendor have their own advantages and disadvantages. Companies should carefully consider their specific needs, resources, and goals before making a decision.
The decision to develop an AI in-house or obtain it from a specialist AI vendor depends on several factors, including:
In-house expertise: If the company has the necessary in-house expertise, such as data scientists, machine learning engineers, and software developers, it may be more cost-effective to develop the AI in-house.
Budget: Developing an AI in-house can be a significant investment, both in terms of time and money. If the company has limited resources, it may be more cost-effective to obtain an AI solution from a vendor.
Time to market: Obtaining an AI solution from a vendor is generally faster than developing it in-house, as the vendor has already done the development work and can provide a ready-made solution.
Customisation needs: If the company requires a highly customised solution, it may be more effective to develop the AI in-house, as vendors may not be able to provide exactly what the company needs.
Maintenance and support: Developing an AI in-house requires ongoing maintenance and support, which can be time-consuming and expensive. Obtaining an AI solution from a vendor usually includes ongoing maintenance and support as part of the package.
What should recruitment businesses look for when looking for an AI solution?
When considering externally developed AI solutions, recruitment businesses should take the following factors into account:
Functionality: Ensure that the solution meets their specific requirements and can perform the tasks that are necessary for their recruitment process.
Accuracy and fairness: Look for a solution that has been tested and validated to ensure that it is making accurate predictions and avoiding bias.
Integration with existing systems: Consider the compatibility of the solution with the company’s existing recruitment software and HR systems.
User-friendliness: Ensure that the solution is easy to use and that the vendor provides adequate training and support.
Scalability: Consider the vendor’s ability to support the company’s growth and increase in volume of recruitment processes.
Data privacy and security: Ensure that the vendor has adequate measures in place to protect candidate data and comply with relevant data protection regulations.
Cost: Consider the vendor’s pricing model and ensure that it fits within the company’s budget.
Vendor reputation and track record: Look for a vendor with a good reputation and a proven track record of delivering high-quality AI solutions in the recruitment industry.
If developed in-house, what should recruitment businesses do when training their AI?
We recommend focusing on the following steps:
Define clear objectives and use cases for the AI: What tasks should the AI be able to perform and what problem should it solve?
Choose appropriate data sets: Ensure that the data used for training the AI is diverse, relevant, and reflects the target population.
Develop and implement ethical guidelines: Consider the ethical implications of AI-driven recruitment, such as avoiding bias in decision-making, protecting candidates’ privacy, and ensuring fairness and transparency.
Validate the model: Use appropriate evaluation metrics to ensure that the AI is making accurate predictions and adjust the model as needed.
Continuously monitor and improve the AI: Regularly assess the performance of the AI and make improvements as needed to maintain its accuracy and usefulness.
Foster a culture of collaboration and transparency: Encourage open communication and collaboration between recruiters and the AI team to ensure that everyone is working towards the same goals.
Will AI impact the recruitment industry by causing job losses?
AI has the potential to impact job creation both positively and negatively. On one hand, it can automate certain tasks, which may lead to job losses in certain industries. On the other hand, it also has the potential to create new jobs and industries, such as those related to developing, deploying, and maintaining AI systems. Additionally, it can improve efficiency and productivity, leading to economic growth and the creation of new job opportunities. One can expect that the net impact of AI on job creation will depend on various factors, including the speed of adoption, government policies, and the ability of workers to acquire new skills to adapt to a changing job market. If you’d like to read about a recruitment experts views on AI, see our interview here with Louise Triance From UK Recruiter, a leading news and networking platform.
What is the guidance around the use of Artificial Intelligence?
Many governments have issued guidance around the use of AI in the private sector. The specifics can vary greatly depending on the jurisdiction, but generally governments aim to ensure the responsible and ethical development and deployment of AI. This often includes guidelines on transparency, fairness, safety, and accountability. Several countries have national AI strategies that outline their plans for ensuring responsible development. The European Union and organizations such as the Organisation for Economic Co-operation and Development (OECD) have also developed principles for the ethical use of AI.
The UK announced a national strategy that outlines its plans to ensure responsible and ethical development and deployment of AI. This includes guidelines on transparency, fairness, safety, and accountability. The UK’s Information Commissioner’s Office (ICO) has issued guidance on AI and data protection, which includes recommendations on data privacy, security, and human rights considerations when using AI. Additionally, the Alan Turing Institute, the UK’s national institute for data science and artificial intelligence, provides guidance and research on responsible AI.
In The Netherlands, the Dutch data protection authority (‘AP’) published a document on artificial intelligence and algorithms in February 2020. The document emphasized the need for supervision of such technologies, and underlined that the principles of lawfulness, fairness, and transparency provide the appropriate basis for allowing the use of AI and algorithms.
In conclusion, Artificial Intelligence certainly looks like it’s here to stay. In 2021, The USA’s International Trade Administration estimated that the UK’s AI market is set to add $880bn to the economy by 2035, investment in artificial intelligence having reached record highs, with AI scaleups raising almost double the amounts raised in France, Germany and the rest of Europe combined. The UK was named as the third country in the world (after the U.S. and China) in terms of investment in AI. Moving forwards, it will certainly be a technology every business should keep in mind when planning for growth and for additions to its tech stack. Yet, this should not be done without also keeping in mind the privacy, security and ethical considerations that we have described above. If you are contemplating using AI in your operations, it’s best to take into account all pros and cons and to consult with relevant authorities in your jurisdiction to determine the specific guidance available.
| 2023-02-09T00:00:00 |
https://www.sonovate.com/blog/the-benefits-and-the-downsides-of-ai-for-the-recruitment-sector/
|
[
{
"date": "2023/02/09",
"position": 26,
"query": "AI job losses"
},
{
"date": "2023/02/09",
"position": 27,
"query": "AI labor market trends"
},
{
"date": "2023/02/09",
"position": 3,
"query": "artificial intelligence hiring"
},
{
"date": "2023/05/01",
"position": 93,
"query": "artificial intelligence hiring"
},
{
"date": "2023/06/01",
"position": 99,
"query": "artificial intelligence hiring"
},
{
"date": "2023/10/01",
"position": 100,
"query": "artificial intelligence hiring"
},
{
"date": "2024/04/01",
"position": 97,
"query": "artificial intelligence hiring"
},
{
"date": "2024/05/01",
"position": 94,
"query": "artificial intelligence hiring"
},
{
"date": "2024/10/01",
"position": 97,
"query": "artificial intelligence hiring"
},
{
"date": "2024/11/01",
"position": 92,
"query": "artificial intelligence hiring"
},
{
"date": "2025/01/01",
"position": 91,
"query": "artificial intelligence hiring"
}
] |
|
The Impact of Automation on the Automotive Workforce
|
The Impact of Automation on the Automotive Workforce: A Discussion on Job Losses and Skills Reallocation
|
https://vocal.media
|
[] |
One of the most obvious impacts of automation is job losses. With robots and other automation tools being used to perform many of the tasks previously done by ...
|
Automation has been a major driving force behind many industries, and the automotive sector is no exception. With the rapid advancement of technology and the increasing use of robots and other automation tools, the automotive workforce is facing significant changes that are reshaping the nature of work and skills required in the industry. In this article, we will delve into the impact of automation on the automotive workforce, and explore the job losses and skills reallocation that have arisen as a result.
One of the most obvious impacts of automation is job losses. With robots and other automation tools being used to perform many of the tasks previously done by human workers, there has been a significant decline in the number of jobs available in the automotive industry. For example, many assembly line jobs that were once done by hand have been replaced by robots that can work faster and more accurately. As a result, many workers who were once employed in these jobs have found themselves out of work and in need of new skills.
However, it's not all bad news. While automation has led to job losses in some areas, it has also created new opportunities in others. For example, the development of electric and autonomous vehicles has led to a need for workers with skills in electrical engineering, software development, and data analysis. These are high-demand, high-paying jobs that offer a much better future for workers than traditional assembly line jobs.
Moreover, the impact of automation on the automotive workforce extends beyond just job losses and new opportunities. It also involves a significant reallocation of skills. Workers who once performed manual tasks are now being asked to learn new skills, such as programming and data analysis, to keep pace with the changes in the industry. This has led to a need for retraining and upskilling programs, which are helping workers transition into new roles and become more productive and valuable in the new automotive landscape.
It's worth noting that the automotive industry is not alone in facing these challenges. Automation is affecting many industries and workers around the world, and the impact is likely to become even more pronounced in the years to come. However, there are also many benefits to automation, such as increased efficiency and cost savings, that make it an essential part of the future of work.
Governments and organizations must work together to ensure that the impact of automation on the workforce is managed in a responsible and sustainable way. This could involve providing retraining and upskilling programs to help workers transition into new roles, or supporting the development of new industries that can absorb workers who have been displaced by automation.
In addition, there is a need for greater transparency and communication between employers, workers, and the wider community. Employers need to be open and honest about the changes they are making, and provide support and training to their workers to help them adapt. Workers, in turn, must be willing to embrace new skills and technologies, and to take advantage of the opportunities that automation creates.
The future of the automotive industry is closely linked to the future of work. Automation is playing a major role in shaping this future, and it is essential that all stakeholders work together to ensure that the impact on the workforce is managed in a responsible and sustainable way. With the right support and training, workers in the automotive industry can take advantage of the new opportunities that automation creates, and help build a bright and prosperous future for themselves and the industry as a whole.
In conclusion, the impact of automation on the automotive workforce is complex and multifaceted. While it has led to job losses in some areas, it has also created new opportunities and skills reallocation in others. The key to successfully navigating these changes is to embrace the new technologies and skills required to remain competitive in the evolving automotive industry. By doing so, workers can take advantage of the new opportunities available to them and build a brighter future for themselves and the industry as a whole.
| 2023-02-09T00:00:00 |
https://vocal.media/wheel/the-impact-of-automation-on-the-automotive-workforce-a-discussion-on-job-losses-and-skills-reallocation
|
[
{
"date": "2023/02/09",
"position": 29,
"query": "AI job losses"
}
] |
|
Why Your Clients Need EPL Insurance
|
Why Your Clients Need EPL Insurance
|
https://www.coalitioninc.com
|
[] |
... losses that might stem from employee lawsuits. One of these steps might include purchasing Employment Practices Liability Insurance (EPLI). This insurance ...
|
What is Active Insurance? The first insurance to help actively assess, prevent, and respond to cyber risk with security tech and broad coverage.
| 2023-02-09T00:00:00 |
https://www.coalitioninc.com/topics/why-your-clients-need-employment-practices-liability-insurance
|
[
{
"date": "2023/02/09",
"position": 88,
"query": "AI job losses"
}
] |
|
6 Real-world examples of machine learning in recruitment
|
6 Real-world examples of machine learning in recruitment
|
https://www.celential.ai
|
[] |
We cover how to use machine learning in recruitment with real-world use cases, plus the potential downside of relying on the technology too much.
|
In the 1970s, job seekers were advised to include personal details in their resumes – such as height, marital status, and age.
In the 1980s, candidates came to interviews with shoulder pads and studied up for typing tests .
In the 1990s, the internet job board was finally invented — though it took a while to catch on. Half of the job seekers in 1997 still found a job through newspaper ads.
The recruitment process has come a long way since then. And it is undergoing another fundamental shift today — thanks to advanced technologies like AI and Machine Learning. Companies are leveraging these techniques to eliminate manual work, gain insights into talent, and make better hires.
Whether your company has high-volume hiring needs or is trying to do more with less, here is everything you need to know about Machine Learning in recruitment. We’ll cover how the technology works and how to leverage it in each part of the hiring process, with real-world use cases plus the potential downside of relying on the technology too much
What is machine learning?
Machine Learning applies advanced optimization algorithms to produce state-of-the-art AI that solves complex real-world problems. The latest deep learning has demonstrated the capability to deliver AI that performs similarly or better than human experts.
Here’s why Machine Learning solutions are game changers in the recruiting process.
How does Machine Learning work?
Machine Learning works by ingesting large amounts of data, which it uses to identify patterns and relationships. The system then uses these patterns to make predictions or take actions that it wasn’t explicitly programmed to do (i.e., “learns”).
Today, Machine Learning often relies on Deep Learning techniques, or the creation of artificial neural networks, to model and solve complex problems. These networks are inspired by the structure and function of the human brain and contain more layering, complexity, and abstraction than older machine learning models.
source: Orhan G. Yalçin
There are three main types of Machine Learning. That includes:
Supervised learning : The algorithm is trained on a labeled dataset, where the “correct” output is already known. For example, say that you want to teach a Machine Learning algorithm to recognize pictures of corgis. With supervised learning, you can show the ML pictures of corgis and non-corgis labeled as such. Over time, the ML will be able to recognize the pattern and predict whether a new picture is a corgi.
: The algorithm is trained on a labeled dataset, where the “correct” output is already known. For example, say that you want to teach a Machine Learning algorithm to recognize pictures of corgis. With supervised learning, you can show the ML pictures of corgis and non-corgis labeled as such. Over time, the ML will be able to recognize the pattern and predict whether a new picture is a corgi. Unsupervised learning: The system is provided with unlabeled data and must find patterns and relationships independently. Unsupervised learning can detect anomalies in financial data, such as fraud or market irregularities. It can also uncover groups or “clusters” within data. Marketers might use unsupervised learning to segment customers based on the types of products they buy or how frequently they purchase.
The system is provided with unlabeled data and must find patterns and relationships independently. Unsupervised learning can detect anomalies in financial data, such as fraud or market irregularities. It can also uncover groups or “clusters” within data. Marketers might use unsupervised learning to segment customers based on the types of products they buy or how frequently they purchase. Reinforcement learning: the system learns by interacting with an environment and receiving feedback through rewards or penalties. A real-world example is the self-driving car, which must decide how to navigate the road, avoid obstacles, and reach its destination. The driving system receives rewards for following the rules of the road, staying within its lane, and reaching its destination quickly and safely. Over time, it learns to make better decisions and improve its performance.
Now let’s get into the specifics of Machine Learning in recruitment.
1. Recruitment Marketing
Recruiters, who typically manage 40–60 requisitions at any time, can use tools like ChatGPT to help speed up the writing of job ads.
There’s also a lot of data that goes into predicting which ads perform well. For example, short job posts under 300 words perform 8.4% better than long ones. 70% of candidates apply on their phones.
Machine Learning can help uncover insights to help you answer questions like where to spend your advertising dollars, how to optimize the structure of your text to get the best results, and the best time of the day to post on job boards.
Use Case: Textio
Textio is our pick for the most up-to-date recruiting language optimization (and diversity boosting) tool currently on the market.
Textio’s recruiting product is fueled by a data set of 70 million+ real-world job listings and hiring outcomes from industries across the globe. It leverages AI and NLP to continually update and optimize the performance of job descriptions, ads, candidate communications, and other recruiting texts.
It also specializes in identifying and eliminating biased languaging, maximizing inclusivity for candidates of all demographics and all backgrounds.
More examples
2/1/23 — ChatGPT leverages AI/ML to write “ads, emails, paragraphs, whole blog posts, or even college papers”
to write “ads, emails, paragraphs, whole blog posts, or even college papers” 11/17/21 — Grammarly raises $200 million to leverage NLP and “AI to generate and optimize ad copy” and other written texts
to leverage NLP and “AI to generate and optimize ad copy” and other written texts 2/1/2023 — The chatbot Globes “ found an idea for a startup, prepared a business plan, developed a product, drafted job ads…”
Particularly when it comes to in-demand tech talent, simply putting up job postings isn’t enough to generate the candidate volume you need. One central pain point Machine Learning can help with is candidate sourcing — where nearly half of recruiters say they spend most of their workweek.
To find candidates, human recruiters need to determine the following:
Is this candidate’s background strong enough to meet our bar but not so strong that we have no chance of recruiting them?
Does this candidate have the right skills? If they don’t list the right skills, can I infer that they do?
Has the candidate previously solved problems similar to those they’ll face in this role?
Finding these answers takes expertise, experience, and time — particularly as roles become more technical and specialized. As a result, finding suitable candidates is challenging to scale.
Celential.ai solves this problem through artificial intelligence and state-of-the-art deep learning models.
To break it down simply:
Celential built a talent graph of 15+ million tech talent across the US, Canada, Latin America, and India.
Graph Neural Networks, complex Machine Learning methods which mimic the structure and function of the human brain, allow Celential’s AI to make complex inferences. It can determine which skills a potential tech candidate possesses, even if they don’t list them publicly. The AI considers the tech stack of the companies they’ve worked for, skills listed on their coworkers’ profiles, JDs for the positions they’ve occupied, and more.
Celential.ai has even taught domain knowledge to its machine learning AI. For example, if a candidate has PyTorch, the AI infers whether the candidate uses it for systems-level engineering versus data science modeling.
As a result, with just a job description to get started, Celential will source and contact top-fit candidates for your roles. Warm candidates will start appearing in just 1-5 days, with no work on your part.
And the insights generated by its AI can tell you predicted skills, career trajectory, level, domain experience, and selectivity — the exact information you need to make a hire.
More examples
7/7/2022 — Beamery’s “AI-based tool conducts unbiased talent searches, considering each individual’s potential and skill set”
“AI-based tool conducts unbiased talent searches, considering each individual’s potential and skill set” 7/7/2022 — ARYA by Leoforce “identifies quality talent for recruiters through data, behavioral patterns, and machine learning”
“identifies quality talent for recruiters through data, behavioral patterns, and machine learning” 8/12/22 — impress.ai ’s “AI-powered platform helps companies identify talent with the most appropriate skills, cutting the time to shortlist by 90%”
Sourcing great candidates and messaging candidates isn’t easy, and that’s only half the battle — how do you convince them to reply?
With tech talent receiving hundreds of messages daily, personalization is the key to cutting through the noise.
Yet while personalized messaging can significantly increase your reply rate , it is tough for busy founders and hiring teams to achieve at scale — unless AI and machine learning can do it for them.
The key to Celential.ai’s personalized candidate outreach is the data in its tech talent graph of 15+ million profiles enriched by Machine Learning. The AI platform leverages this data to generate unique, highly personalized messages to pitch roles to candidates.
Once a candidate replies, Celential uses Natural Language Processing to analyze a candidate’s reply, determine the best response, and then create it. It uses sentiment analysis to scan for indications of positivity within a message, then hones in on a number of common recruiting scenarios.
Once the Machine Learning system understands the scenario, it crafts an appropriate response or notifies human recruiters that there is an opportunity to engage with the candidate personally. This frees up time for recruiting teams that would normally be spent reading emails, following up on messages, and answering common queries.
More examples
2/29/2022 — At Jobvite , “AI is being used to automatically send outreach messages to candidates in a company’s database.”
, “AI is being used to automatically send outreach messages to candidates in a company’s database.” 7/7/2022 — Bullhorn “integrates AI into its talent platform, allowing recruiters to reach out to candidates with automated messages”
4. Resume Screening
Early resume screeners got a bad rap for screening out highly qualified candidates, being vulnerable to simple hacks, and failing to read formats outside of the word document.
Those of us who have ever looked for a job are likely familiar with the pain of uploading your resume… than painstakingly typing out the same information info into an employer’s 15-page online form.
However, resume screening technology has come a long way over the past few years and is now indispensable to an efficient talent acquisition process. This is also good news for recruiters, who spend 23 hours on average reading resumes for every hire they make.
Use case: Hiration
Hiration provides a two-in-one complementary solution for job seekers and employers.
Its Machine Learning and NLP-powered tools help candidates quickly build the perfect resume and present themselves in the best light to companies. They also help optimize resumes to pass through employers’ AI recruitment tools and ATS.
Machine Learning algorithms are then used to match candidates with job descriptions predicted to have the best chance of success.
“Making sense of data at this scale has only become possible with the recent advancements in natural language processing and deep learning,” said CEO Aditya Sharma. “Using OpenAI’s GPT-3 and other in-house machine learning models, we’ve developed a career assistant that guides job seekers in real-time, while they are crafting their resume or preparing for their interview.”
For their part, employers use Hiration in the recruitment process to source, shortlist, and screen candidates. And as the company continues to input data on employees and employers, Hiration’s mutual-fit matching algorithms continue to improve.
More examples
12/20/22 — SmartRecruiters “uses AI to screen resumes and past candidates to identify top candidates”
“uses AI to screen resumes and past candidates to identify top candidates” 1/31/2023 — ChatGPT can “assist with resume screening, candidate questions, and scheduling interviews”
Chatboxes, AI assistants, and automated messaging systems can leverage Machine Learning to replace the conversations and scheduling normally done by administrative assistants and coordinators:
Replying to Candidates : Machine learning algorithms can determine whether candidates are interested, not interested, or requesting more information and shoot back a reply at any hour of the day.
: Machine learning algorithms can determine whether candidates are interested, not interested, or requesting more information and shoot back a reply at any hour of the day. Scheduling Interviews: The task of comparing calendars, emailing back and forth, and reminding candidates to show up can now all be performed by AI.
The task of comparing calendars, emailing back and forth, and reminding candidates to show up can now all be performed by AI. Extending offers: Machine Learning can help determine appropriate salaries based on market data, generate offer letters, and manage to onboard.
“Say hello to your next best hire,” proclaims Paradox.ai.
According to the company, that’s Olivia, an AI assistant hireable by the hour. Olivia can automate, answer, screen, schedule, and onboard candidates for companies.
Paradox.ai’s NLP algorithms were programmed to create a more human touch and improve the candidate experience. Its AI chat box technology ingests data and uses pattern matching to understand speech and pick up signals about mood and personality. Candidates interact with Olivia as they would with a recruiter or hiring manager, answering questions such as how many years to experience they possess.
Paradox.ai recently acquired Israeli AI chatbox startup spetz.io to further enhance the development of its AI and Machine Learning technologies.
More examples
1/27/23 — Humanly, XOR, Eightfold, Brazen, HireVue, Symphony Talent, Ideal, CEIPAL, iCIMS, and Sense included in a study released on recruitment chatboxes, or “program that simulates and processes human conversation, either written or spoken format with the help of artificial intelligence and machine learning”
One of the most frequently underestimated costs in the recruitment process is the time spent not just by recruiters but by hiring managers and their teams. This is particularly true for engineering roles — a big chunk of the total cost to hire a software developer goes to the hours that highly-paid software engineers sink into conducting coding exams to assess candidates.
Given a role, targeted skills, and seniority level, Machine Learning can help generate evaluations for technical expertise, cognitive ability, cultural fit, domain knowledge, and language proficiency.
As Machine Learning technology grows ever more advanced, behavior analytics techniques, Computer Vision, and Natural Language Processing can even help measure soft skills, culture fit, and communication ability through video interviews .
Use Case: HackerRank
HackerRank has evaluated over 40% of the world’s entire developer population, and all that data went into creating its AI tools for evaluating and hiring candidates.
These tools can score and rank candidates, offer test feedback, and perform more granular skill assessments for companies who need detailed information on candidates’ specific competencies.
To create an assessment score, HackerRank’s Machine Learning model considers factors such as how long developers spent on the test, the coding language they used, and how often they had to run a piece of code.
Its Tech Talent Matrix also helps companies put assessment scores into context and benchmark against peers — providing valuable insights for employers.
More examples
11/14/2020 — HireVue has a “proprietary algorithm to determine which candidates are ideal for a specific job by analyzing their vocabulary, speech patterns, body language, tone, and facial expressions”
has a “proprietary algorithm to determine which candidates are ideal for a specific job by analyzing their vocabulary, speech patterns, body language, tone, and facial expressions” 4/28/2022 — MyInterview evaluates candidates with an “ML-trained database of tens of thousands of interviews, with each interview rated by a team of four different behavioral psychologists based on specific criteria”
Pitfalls of Machine Learning in Recruitment
Machine Learning insights can be extremely valuable to companies. However, mistakes can cost you time, qualified candidates, and reputation.
As AI, Blockchain, the Internet of Things, Robotic Process Automation, and Virtual Reality continue to transform the recruiting industry, here are some common pitfalls to watch out for.
Algorithm bias in the recruitment process
In 2018, Amazon discovered a big problem: it’s Artificial Intelligence recruiting tool did not like women .
The experimental hiring tool used Machine Learning to automatically rate each applicant with up to five stars — much like customers rate products while shopping at Amazon.
The problem was that the AI system was trained on resumes submitted to Amazon over the past 10 years, which were overwhelmingly from men. This caused the AI to downrate resumes containing words such as “women” or “female” and to prioritize male candidates.
While Amazon has since discontinued the problematic tool in its recruitment process, there are many other examples of AI systems that display bias against different ethnic groups , non-English-language speakers , and people with disabilities .
Companies can prevent algorithm bias with the following:
Diversity training data , including resumes and profiles from individuals of different gender, ethnicity, and educational backgrounds
, including resumes and profiles from individuals of different gender, ethnicity, and educational backgrounds Fairness constraints and human oversight to prevent the algorithms from making biased decisions based on protected characteristics
to prevent the algorithms from making biased decisions based on protected characteristics Regular auditing and testing to continually monitor and improve decision-making
to continually monitor and improve decision-making Transparency so that biases can be identified and addressed.
Lack of personal connection in the hiring process
Automation not performed with care (such as in outreach messages, scheduling chatboxes, or employment assessments) can feel annoying, impersonal, and robotic — precisely the opposite effect as desired.
Candidates want to feel valued and unique — they don’t want to feel like interchangeable widgets on the factory line.
When done well, AI can team up with humans by eliminating the repetitive, manual tasks in the recruitment process — freeing up recruiters to build strong relationships with candidates
Gaming the system
There are many ways in which candidates can optimize their resumes for more points in an automated hiring system — such as by adding keywords from a job description.
In extreme cases, some candidates have turned to hacks such as adding keywords or even the whole JD to their resume in white-colored or tiny text — able to be picked up by the tool but not the human eye.
Some hiring tools have been trained to spot these hacks, but clever candidates sometimes will just outwit the machine.
No bandwidth to learn a new artificial intelligence tool
Tool fatigue is real. Companies purchase shiny (and pricey) new software, licenses go unused, and employees waste time jumping from tool to tool.
If that sounds familiar, Celential.ai offers an AI-driven Virtual Recruiter service that sources, vets, and engages top-notch, diverse candidates for technical and sales roles.
We deliver ready-to-interview candidates to customers directly. No learning curve or tools to learn. Just results!
| 2023-02-09T00:00:00 |
2023/02/09
|
https://www.celential.ai/blog/machine-learning-in-recruitment/
|
[
{
"date": "2023/02/09",
"position": 10,
"query": "machine learning job market"
}
] |
AI in Retail Market Size & Forecast 2023-2033
|
AI in Retail Market Size & Forecast 2023-2033
|
https://www.futuremarketinsights.com
|
[] |
The adoption of artificial intelligence in retail is expected to surpass USD 127.09 billion by 2033. Future Market Insights forecasts the demand for artificial ...
|
Artificial Intelligence in Retail Market Size and Share Forecast Outlook for 2023 to 2033
The global artificial intelligence in retail market is forecast to reach USD 10.76 billion in 2023. The adoption of artificial intelligence in retail is expected to surpass USD 127.09 billion by 2033. Future Market Insights forecasts the demand for artificial intelligence in retail to grow by 28% CAGR between 2023 and 2033.
Key Factors Propelling the Demand for AI in Retail
In the coming years, the retail industry is set for an important overhaul thanks to the advent of AI. This innovative technology has the potential to transform the industry from cost elements to shopping participation. With e-commerce and AI working hand in hand, and the recent coronavirus outbreak boosting e-commerce growth rates, sellers must adopt AI as soon as possible. Planning for the integration of AI must be done with both technology and company strategy in mind.
The main advantage of AI in the retail industry is its ability to take over tedious, repetitive tasks and help consumers. Just like how AI has increased productivity in the workplace, the usage of AI in retail leads to the same results. AI-driven logistics help determine optimal delivery routes, while robots can assist with order selection and packing, freeing employees to focus on other important tasks.
Transforming Retail Through AI: Enhancing Experience, Personalization, and Efficiency
Artificial intelligence (AI) has become a game-changer for various industries, including healthcare, automotive, and manufacturing. As Gen Z takes over as the dominant consumer base, their strong preference for online shopping has made AI a must-have tool in the retail market. With cashier-less checkouts powered by computer vision and big data analytics, retailers are revolutionizing the shopping experience.
The growing popularity of online shopping trends, driven by the tech-savvy and mobile-friendly Gen Z population, has created a huge demand for AI solutions and services in the retail market. AI is not only transforming the shopping experience with cashier-less checkouts, but it's also making retail operations more efficient and intelligent. The future of retail is looking brighter with the integration of AI.
Key Barriers to Widespread AI Integration in Retail Environments
Despite the continued investment in AI technology by leading retail companies, there are still numerous barriers to the widespread adoption of AI in the retail sector. Small and medium-sized businesses and start-ups may face challenges in terms of infrastructure and technological know-how, while high implementation costs present a significant challenge for small retailers. However, the potential benefits of AI in the retail market cannot be ignored, particularly with the increasing usage of IoT, Big Data analytics, and e-commerce marketing.
The retail industry is anticipated to experience a wave of growth thanks to the increasing popularity of AI. Advancements in computer vision and other technologies are paving the way for new retail opportunities in areas such as customer experience, demand forecasting, and inventory management. With AI focusing on planning and product recommendations, the growth of AI products and services across various industrial domains and verticals is fueled by big data analytics.
Artificial Intelligence in Retail Market Estimated Year Value (2023) USD 10.76 billion Artificial Intelligence in Retail Market Projected Year Value (2033) USD 127.09 billion Value CAGR (2023 to 2033) 28%
2017 to 2022 Global AI in Retail Trends Compared to Forecast from 2023 to 2033
The retail industry is undergoing a promising transformation with the adoption of artificial intelligence. This new technology is changing the way companies track their operations, improve their strategies, and engage with customers in the digital world.
The growth of the global AI in retail market is driven by factors such as the increasing number of internet users and smart devices, rising awareness about AI and big data & analytics, and government initiatives towards digitization. The adoption of multichannel or omnichannel retailing strategy, untapped opportunities to boost sales efficiency, and enterprises' need to streamline their processes. In addition, the growing desire to enhance the end-user experience and take advantage of market dynamics is also contributing to the growth of global AI in retail market.
During the forecast period, the market is projected to experience substantial growth compared to the period of 2017 to 2022. Artificial intelligence in retail market is likely to record a 28% CAGR from 2023 to 2033, in comparison to the 19% CAGR registered from 2017 to 2022.
Year Market Growth during 2023 to 2033 2025 17.64 USD billion 2028 36.99 USD billion 2032 99.29 USD billion
Short term (2022 to 2025): With the growing number of internet users and the widespread adoption of smart devices, there is a growing demand for AI in retail. This is because AI-powered applications can provide enhanced customer experiences through personalized recommendations, product searches, and intelligent pricing algorithms.
Medium term (2025 to 2028): The increasing awareness about the benefits of AI and big data & analytics is driving growth in the global artificial intelligence in retail market. Retailers are recognizing the potential of AI to streamline their operations, improve customer engagement, and drive business growth.
Long term (2028 to 2032): Governments around the world are investing in digitization initiatives to promote the adoption of AI in retail. This includes providing financial incentives and subsidies, setting up innovation centers, and promoting digital literacy. These initiatives are creating a supportive environment for the growth of AI in the retail sector, thereby contributing to the overall growth of global artificial intelligence in retail market.
Analysis of Top Countries Utilizing and Innovating in AI-Powered Retail Technologies
North America: A Dominant Force in AI in Retail Market
North America is poised to lead the AI retail market, with the United States expected to grow at a CAGR of 5.8% during the forecast period and reach a value of USD 64 billion by 2033. The growth is driven by the rising number of businesses adopting AI and the presence of key players in the region, along with increased adoption of cloud services and investments in new technology.
North America is leading the way in terms of AI in retail, with the region dominating the global revenue share. Retailers in the region are leveraging customer data to improve customer service and boost efficiency. The United States is at the forefront of AI adoption, with high levels of investment in technology and the emergence of new startups and small enterprises in response to growing demand.
Asia Pacific Gears Up for AI in Retail Revolution
The Asia Pacific region is poised for rapid growth in the AI in retail market, driven by the rapidly growing digitalization of the retail industry. The region is undergoing an important transition, which is fueling demand for advanced technologies to improve operations and customer experience. For example, China has secured a 23.4% share of AI investments in the commerce and retail industry, according to SAP SE analysis. India is expected to see a leading growth due to the increasing demand for automation tools to improve decision-making and operations.
China AI in the retail industry is projected to grow at a CAGR of 5.46% and reach a value of USD 5.4 billion during the forecast period. The growth is driven by the expansion of the IT business, increasing industrial automation, and the growth of internet penetration and mobile devices.
Japan and South Korea: Emerging Markets for AI in Retail
Japan AI in the retail industry is expected to grow at a CAGR of 5.6% and reach a market value of USD 6.3 billion during the forecast period, driven by increasing industrial production and the expansion of mobile technologies. South Korea is expected to see a CAGR of 4.8%, driven by the growing consumer shopping experience and the implementation of smart building infrastructures.
The United Kingdom: A Promising Market for AI in Retail
The United Kingdom is expected to grow at a CAGR of 4.66% during the forecast period, driven by the emergence of IoT and Machine-to-Machine technologies and the increasing demand for research and industrial capacity in the region. AI in retail has become an integral part of the growing IoT market in the United Kingdom, with the region focusing on digitization post-Covid-19 by using AI and 5G networks.
Europe is expected to rank second in terms of AI in retail market share, with key retailers in the cosmetics, fashion, and apparel sectors actively investing in advanced technologies to improve the customer experience. The European technology industry saw a 26.7% rise in the AI segment in Q1 of 2020, fueling demand for AI in the retail industry.
Artificial Intelligence in Retail Industry Analysis by Solution, Deployment, and Application
Disrupting the Retail Landscape: The Rise of AI Solutions and Services
In terms of market share, the solutions segment is projected to hold a 73 % share, accounting for a substantial portion of the global AI in retail market. Retailers are turning to automated solutions to tackle complex management challenges, streamline supply chain operations, improve logistics, and enhance the customer experience.
However, the services segment is not far behind, with a significant growth rate forecast over the next few years. The increase in demand for AI services is attributed to the increasing popularity of AI solutions and their ability to drive revenue growth, improve customer experience, reduce human error, speed up innovation, and create intelligent functions.
Chatting with AI: ML leads the Market, NLP on the Rise
According to market research, machine learning (ML) has acquired a leading revenue share of over 32% among the different AI technologies, such as natural language processing, image & video analytics, chatbots, and swarm intelligence. The increased precision and flexibility of ML technology are contributing to its expanding growth. With its ability to rapidly and deeply serve data, ML is ideal for providing personalized experiences to customers. It also helps merchants streamline their supply chain strategies and demand projections to increase inventory productivity. Amazon Sage Maker, a fully managed service, enables the deployment of machine learning models for various activities ranging from customer experience to predictive analytics.
Natural language processing (NLP) is also on the rise, as the demand for data analysis and AI-powered chatbots increases. The market for NLP is expected to grow rapidly during the forecast period, with a market share estimated to be 15%. As AI technology continues to progress, NLP plays a critical role in providing more accurate and efficient communication for various applications.
CRM Category to Dominate the Market, Virtual Assistant Segment to Register High Growth
The AI in the retail market is divided into various applications, including customer relationship management (CRM), inventory management, supply chain & logistics, product optimization, payment & pricing analytics, in-store navigation, virtual assistant (VA), and others. CRM dominates the revenue share and is expected to continue growing, with a pressing need to improve customer service and retention. With the use of chatbots, search engines, and other AI technologies, retailers are aiming to establish strong customer relationships and foster loyalty.
Virtual assistant technologies have enormous growth potential in the retail industry, offering solutions for streamlining the supply chain, invoicing, ordering inventory, and bookkeeping. As a result, virtual assistance is expected to see significant growth in the forecast period, solidifying its position as a key player in the AI retail market.
Disrupting the Game: An Insight into the AI-Fueled Retail Industry's Top Players
The global artificial intelligence in retail market is becoming increasingly competitive, with new players entering the arena and established companies investing in cutting-edge technology. Leading players such as Amazon, IBM, Microsoft, and Salesforce are dominating the market with their advanced AI solutions. These companies are making significant investments in R&D to stay ahead of the curve and maintain their dominant positions.
In addition, emerging players such as H2O.ai, Neurala, and Vicarious are disrupting the market with their innovative solutions. These start-ups are attracting investments from leading venture capital firms and making a significant impact on the industry with their ground-breaking technologies.
Established players in the retail sector, such as Walmart, Tesco, and Alibaba, are also making significant investments in AI technology to improve their customer experience and operations. These retailers are embracing AI to enhance their competitiveness and maintain their dominant positions in the market.
Overall, artificial intelligence in retail market is expected to continue its growth trajectory, with increasing competition among established and emerging players. As AI technology continues to evolve and new solutions emerge, companies must stay ahead of the curve to remain competitive in this rapidly changing market.
Leading Providers of Artificial Intelligence Solutions for Retail
Amazon Web Services
Oracle
IBM Corporation
Microsoft
SAP SE
Salesforce Inc.
NVIDIA
Google LLC
Sentient Technology
ViSenze
Intel
Recent Developments in the Market:
| 2023-02-09T00:00:00 |
https://www.futuremarketinsights.com/reports/artificial-intelligence-in-retail-market
|
[
{
"date": "2023/02/09",
"position": 55,
"query": "workplace AI adoption"
}
] |
|
Will AI Take My Job in 2023 and Beyond
|
Will AI Take My Job in 2023 & Beyond? How Safe is Your Job?
|
https://www.beyond.agency
|
[] |
From content writing to creative media, AI has quickly become smarter and more capable of replacing jobs we never thought it could...
|
In the last year, AI has skyrocketed in ways no one could have predicted. Last year, we queried the same question: will AI take my job, and 12 months later, here we are again pondering the advancements in this mind-blowing field… The Introduction of AI From content writing to creative media, AI has quickly become smarter and more capable of creating better user experiences. Not only does AI save us time by automating tasks, but it also helps us better understand patterns in data, especially through powerful platforms like Ramp CRM and industry-leading tools that are integrating AI into their analytics and content creation tools. AI has made impressive advances towards basic autonomous decision-making that continues to prove useful in countless applications that not only make life easier but more secure as well. In short, AI is revolutionising our world in extraordinary ways and 2023 shows no signs of slowing down. The Impact of AI AI technology has been the focus of much discussion and debate, with some voicing worries that robots will eventually supplant human workers. Although it is true that AI may cause changes in certain industries, these effects can be managed responsibly to ensure a net gain in job creation while also providing benefits such as improved efficiency and safety. With the looming threat of automation, you may be wondering if your job is at risk. The dawn of Artificial Intelligence (AI) has been a dramatic shift that is changing the way we live, promising to revolutionise many industries and everyday life, but it also presents challenges for workers as certain jobs are replaced with digital labour. Don’t worry though, companies won't just abruptly replace employees with robots! A gradual transition will ensue as robotic assistance and human labour are tested side-by-side to discern whether an automated process would work better in certain industries or particular roles. Although one thing is for sure; ultimately, AI will eventually be implemented in every industry and every job role, some sooner that others, in order for us all to reap its rewards. Job roles AI was always going to replace! Last year, we looked at 12 jobs on both sides of the fence; those that will not be replaced by AI within the next two decades (or so we thought…) and others that come with a high risk score for being susceptible to robot takeover! Our team has done thorough research into these exact same roles just 1 year on and the results are fascinating - automation's ever-increasing power is only just beginning! 1. Customer Service Executives AI has opened up an exciting new world of possibilities businesses can explore to boost customer service. AI-enabled chatbots are increasingly going beyond simply answering basic questions to providing advanced solutions and creating personalised interactions with customers. In the near future, these AI-based customer service executives will become the norm, backed by sophisticated algorithms that understand customer behavior and conversations in natural language. By replacing mundane tasks with AI-driven automation, customer service executives will be able to focus more on important aspects like managing complaints and tailoring services based on each individual's needs. This revolution in the customer service industry is a step towards a smoother and more efficient customer experience! Surprisingly, the risk factor of automation for customer service has dipped slightly between 2022 and 2023 data, however, the potential for customer service roles to be completely replaced by AI in the foreseeable future is incredibly high. Companies are taking advantage of AI-driven customer service to improve their customer service offerings, including faster response times, improved accuracy and more personalised interactions with customers. By leveraging machine learning algorithms, companies can analyse customer conversations in real time, providing better insights into the needs of each individual customer. 2. Bookkeeping + Accounting In the near future, AI is set to replace accounting. With increased accuracy and reduced manual labour, automation will drastically improve how businesses keep their finances in check. AI-based systems can analyse huge amounts of data quickly without getting tired or making mistakes. As a result, tasks such as payroll processing and tracking spend on goods and services are becoming effortless. Online accounting systems like Quickbooks and Sage have already taken the world by storm, transforming how small businesses and large enterprises alike manage and monitor their finances, so it’s only a matter of time before they perform every aspect of an accountant’s job; day-to-day reconciliation, corporation tax returns, self-assessments. You name it, AI will do it. In the last year, the risk level of accountants roles has increased from 93% to 100%, suggesting this job role won’t exist within the next two decades! 3. Receptionists With the increasing influence of technology in everyday life, it's no surprise that AI is becoming an increasingly important part of the workforce, and receptionists are no exception. AI will be able to greet customers more quickly and efficiently than ever before, as well as providing tailored responses to customer enquiries. This means fewer long queues at reception desks and faster service for customers, improving both convenience and customer satisfaction. Not only that, but AI-powered receptionist services can be available 24/7, which brings with it greater flexibility for both customers and businesses. It’s no surprise then that this role is at even more risk of automation than it was 12 months ago: 4. Proofreading As technology continues to evolve, artificial intelligence (AI) is making waves in the world of proofreading. Embracing AI for proofreading can save time and money for businesses and organisations, while ensuring written materials are more error-free than ever before. With natural language processing, AI quickly and easily flags typos, spelling errors, incorrect grammar, missing words and other common mistakes which can easily be overlooked by even trained professionals. AI not only provides thorough checks with impressive speed compared to traditional human proofreaders; it also eliminates potential for bias in the editing process. In an age of increased digital communication, with more content creation that ever before, AI proofreading tools are set to transform the speed to market of written pieces, providing a much-needed solution for maintaining accuracy in written work that was previously impossible or extremely tedious with manual methods. As a result we'll all benefit from better communication and ideas being shared without concern over quality errors. AI’s threat to proofreading has increased by 18% over the last 12 months, suggesting this will no longer be a ‘human’ role in the near future! 5. Pharmacy Technicians The field of pharmacy is quickly evolving. With the capabilities of AI, pharmacies and medical centers can streamline their operations and increase accuracy as well as efficiency. AI algorithms can help pharmacy technicians by quickly identifying dosage and medication errors, as well as substitute choices when a drug is not available. This reduces the burden on pharmacists who risk being overwhelmed due to the often large number of patients they are responsible for. Furthermore, AI technology allows for an automated workflow that can detect certain medication errors that often elude human technicians. In other words, AI makes for a more reliable and secure system that many pharmacists rely on in order to provide the best possible patient care. As such, it's easy to see why AI will become increasingly popular in this field and eventually replace human technicians entirely. Although the risk of automation seems tohave decreased over the last 12 months, the role of a pharmacy technician is still very much under threat by AI. Perhaps the sensitive nature of drug prescription and supply has halted AI in this field for now, but we’re sure it will accelerate with advancements in technology. 6. Retail Services AI has great potential to change retail services and make the customer shopping experience even better. AI technologies are already being introduced in many industries, and retail stores are no exception. AI-operated assistants can help customers find what they need without having to wait for an employee - a huge time saver for shoppers! AI-assisted checkouts have become more and more commonplace over the last two decades and the next two decades are set to see this go one step further, despite this surprising result: Amazon Go stores have already eliminated the need for in-store assistants AND checkouts, allowing customers to simply walk in and out of a store to be charged automatically to their mobile device - replacing humans altogether in stores is surely just around the corner? The possibilities of what AI can do in the retail industry are endless and although according to research the risk of complete automation has dropped slightly, AI is surely set to make waves in this space!
7. Courier Services It's no secret that artificial intelligence (AI) is emerging as a powerful force in many aspects of our lives, and its influence extends to the increasingly popular world of courier and delivery services, making them more efficient and intelligent than ever before. It opens up opportunities for businesses to automate their operations, take advantage of digital payments, track parcel locations with precision, and manage customer relations better. Thanks to AI advancements, courier and delivery businesses can rely on cutting-edge technology like advanced algorithms, natural language processing, computer vision, machine learning, data analytics and more to reduce costs while increasing user satisfaction. This opens up an array of exciting possibilities for future innovations that could tremendously improve the way people access goods they need every day. 8. Surgical Assistants AI is revolutionising the medical world and transforming healthcare as we know it. From robot-assisted procedures to AI-based diagnostics, intelligent machines are becoming increasingly involved in surgical care, providing doctors with powerful new tools to get better outcomes for their patients. AI doesn't just mean faster, more efficient surgeries - it's also changing the way healthcare providers specialise and collaborate. Healthcare professionals now have unprecedented access to data and insights that lead to better decision making and, ultimately, more successful treatments. Although not an incredibly at-risk role right now, risk level has steadily climbed in the last 12 months and AI advancements in science and technology are continuing at a rapid pace. Understandably, it’s an area of utmost impact on human life so it will need a rigorous testing process. As the path towards a smarter, more sophisticated healthcare system continues to unfold, AI will undeniably play a major role in taking it there. 9. Military Pilots & Personnel With the growing popularity of artificial intelligence, it is becoming increasingly clear that AI will take the place of pilots and military personnel in the years to come. Since driverless cars, trains and tubes already exist, a natural extension is to aviation! With robots and machines that are programmed with special skills and knowledge, they will be able to perform aerial operations and strategic maneuvering more efficiently than humans. Not only that, but they could be used to scout ahead in uncertain areas without putting anyone’s safety at risk. Already, experts have tested out these robots for their capabilities, resulting in accelerated adoption of AI in this field: 10. Taxi + Bus Drivers It's only natural that AI will influence taxi and bus drivers in the near future. Scheduling redies through apps like Uber has become second nature, and driverless cars already exist - put 2 and 2 together and you get 4! Everything from booking cabs to ensuring customer satisfaction will be handled by a software program powered by AI, making it easier than ever for passengers to enjoy their rides. We could soon be traveling around in connected autonomous vehicles with AI that provides us with personalised, directed travel experiences. The roles of taxi and bus drivers will change significantly over time as AI takes over some of their responsibilities, leading to more convenient journey experiences for everyone involved. Although there’s een a slight fall in automation risk, once driverless cars become mainstream, there’s no stopping this role from being replaced. 11. Market Research Analysts In the past, market research analysts were seen as an essential part of the research process and required to collect, analyse, and disseminate valuable insights for businesses. However, with the rise of Artificial Intelligence (AI), all that is about to change. AI technology provides access to a never before seen wealth of information on consumer behavior that can be highly predictive in nature. With AI handling routine tasks such as gathering and crunching data, it won’t be long until analysts turn into a thing of the past. This powerful combination of AI and Machine Learning is on its way to becoming a revolutionary tool in understanding customer needs and driving product innovation, gradually replacing humans in this field: 12. Security Guards As technology continues to advance, many people are now considering how and why artificial intelligence (AI) will replace traditional human security guards. AI can provide increased safety with its greater accuracy and ability to predict, identify and respond to warning signs and threats quickly. AI systems are reliable and less prone to errors or emotional responses which may lead to ineffective solutions for security problems. Deploying AI-driven solutions to physical security requirements offers a tremendous opportunity to automate and improve the existing security practices of businesses, residences, offices and retail stores. Additionally, AI provides increased flexibility, allowing companies more control over shifting resources with changing personnel requirements. This development not only promises considerable cost savings but also reduces the risk of compromised safety from human elements such as negligence or bias in judgement. In short, AI has what it takes to revolutionise physical security applications: dependability, accuracy and overall effectiveness, which is why this dip in risk has us all surprised! Perhaps we’re still a little cautious of completely replacing humans who we feel we have a personal connection to and can rely on… Jobs AI won’t replace anytime soon (or so we think)… AI is making tremendous strides and its potential to replace certain human jobs has sparked an interesting discussion. Although robots can be programmed for standard tasks, their ability to think outside the box or handle social situations will remain a job exclusive to humans - requiring creative problem-solving skills that are beyond current AI capabilities. As we continue discovering more about how far artificial intelligence technology can go, it's clear there will still be roles out there only people - with all our thoughtful ingenuity - could do! 1. Chief Executive Officers - CEOs Artificial intelligence has come a long way in its ability to make decisions, learn from past experiences, and interpret data. However, the kind of leadership that an AI can deliver is unlikely to match the kind of dynamic direction provided by a human CEO. A CEO is a figurehead that guides decision making, but also represents the company externally. AI does not possess empathy or the capability of gauging employees' morale and motivation for greater production. At best, AI might bring more efficient executive decisions to businesses, but it lacks the subtlety to inspire innovation within an organisation that a flesh-and-blood leader can wield with confidence and effective communication strategies. In addition, while advances in AI technology may allow machines to be ever more reliable administrators, it cannot replace the skills necessary to evaluate solutions beyond those programmed into it by its creators. Ultimately, when a real crucial decision needs to be taken in the modern era there remains no substitute for a capable CEO to lead us through these often tricky waters. For reason, CEOs are safer than ever, with a dip in risk factor as we look to humans for leadership: 2. Teachers + Educators When it comes to replicating the role of a teacher or educator, AI brings its own unique limitations that make it difficult for it to replace human professionals. Unlike a computer programme, teachers are able to recognise and understand emotional cues, providing personalised support that helps students learn and grow. Not only this, but the relationship between teachers and students allows for more effective learning and for students to better remember the material. Additionally, educators have the ability to adjust their teaching style on the fly depending on how their lessons are received by their students. AI simply cannot match this level of adaptability, making teachers still an invaluable part of every student's learning journey. In short, robots cannot come close to replicating the relationship between educator and student that is so important in ensuring learning takes place. For this reason, AI will not replace teachers or educators in any meaningful way in the near future. 3. Editors Artificial Intelligence seems to be making its way into the editing and publishing world, looking set to replace editors and proofreaders in the not too distant future. AI machines have long been able to recognise grammar and spelling mistakes with incredible accuracy - think back to Microsoft’s early days of ‘spell checker’. But there had been scepticism in whether AI would be able to proof extended text such as novels and white papers, and edit them - the editing part having always been left to a human… Over the last few years, AI has become increasingly precise, plus it’s able to scan documents at an exponentially faster rate than humanly possible, meaning this industry is being taken over faster than we once thought. Ultimately, AI editing offers a much cheaper yet reliable means of editing and proofreading that allows companies to have consistent quality documents at a fraction of the cost. In addition, they can learn from their own mistakes as they review a text multiple times and it continues to become more precise as they gain more experience over time.
4. Event Planners With AI advancing at a rapid rate, it might seem like event planning technology could soon become a thing of the past. However, they’re not yet stealing the role of an event planner who can bring an experience to life in ways that automated systems and AI can’t. For instance, event planners are uniquely able to use their creative skills and problem solving abilities to anticipate and swiftly respond to unexpected problems on the day of an event, something that AI couldn’t do as effectively. Having said that, there has been a small increase in risk-level, suggesting AI is getting better at handling improvisation and organisation: 5. Graphic Designers Creative fields like graphic designers used to feel secure from AI's rise, as we believed it couldn't replicate creativeness. But, the truth is that these modern AI tools are having a major impact on this industry. From generative image synthesis and content creation, creative AI tools have already begun to revolutionise the creative field. We are seeing a major move towards faster creation, with AI having the capability to generate high-quality visuals quickly. It has made the process of creating visuals or content more accessible and cheaper for everyone involved. Creative roles will now need to focus more on innovative design approaches in order to differentiate their work from these automated processes. It’s important that creatives work in harmony with AI to leverage its advantages and produce work that is both practical and original. Creative AI will continue to evolve and its applications in the creative field are sure to increase over time, making this significant risk-level increase a little concerning! 6. Lawyers With AI's current capabilities, legal professionals can access and interpret data faster than ever before, helping them make smarter decisions sooner. Additionally, AI-powered document analysis can save lawyers time spent pinpointing special stipulations in contracts or regulations. And while AI technology is still far from guaranteeing 100% accuracy, some lawyers are beginning to trust machines more than their fellow attorneys in order to settle cases quickly and efficiently. The argument being that AI is less biased than humans, although that’s another story! That said, AI cannot accurately understand the nuances of laws like complex international agreements or interpret human emotions and intentions when it comes to crime and for those things, lawyers will be desperately needed in human form. Though we might not have completely replaced lawyers with machines anytime soon, it’s clear that "machines" will continue to become part of human attorney teams in the years ahead, perhaps moreso on the creation of legal documents or analysis of cases. 7. Marketing Managers Artificial Intelligence (AI) technology has come a long way and is widely used in marketing efforts for businesses today. From predictive analytics to optimising campaigns, AI has become an essential tool for managing the complexities of modern marketing. However, AI on its own is not enough to completely replace marketing managers. AI as we know it requires a competent driver, so although it may speed up the production of content, graphics creation and market analysis, it cannot fulfil the role of a marketing manager who pieces all of the pieces of the jigsaw together. In a marketing environment, AI is great at monitoring the constantly changing algorithms, customer demands and the broader social climate, but it will take more than advanced algorithms to replace skilled marketing managers at this time. Despite the increase in automation risks, the role of a marketing manager is pretty safe for the foreseeable! 8. Computer Scientists AI's advanced algorithms make it an ideal candidate for replacing software developers as AI machines have the capacity to understand instructions and determine optimal solutions. This ability to recognise patterns in data sets makes it exceptionally useful for developing more intuitive interfaces. However, despite its advantages, AI may struggle when tasked with analysing creativity or qualitative factors that are inherent in many software development projects. In order to become a viable replacement for skilled software engineers, AI must continue to learn and evolve over time. It is clear that although AI may eventually be able to supplant some (or even most) roles of a software developer, there are still areas where human expertise will always be needed. 9. Writers + Authors Another interesting field like that of graphic designers… We’d always thought that creative writing would not be taken away from humans any time soon, however, it would appear that this is one of the first industries to experience a complete shake-up from AI. AI technology is being used to create original content such as songs, video clips, news articles, and more. The threat of AI on authors and writers could be seen as a positive development - it is it highly efficient and cost-effective and can open up inspiring opportunities for marketing campaigns - although many talented and experienced authors argue otherwise! AI can help with some of the more tedious aspects of writing, such as researching and brain-storming, freeing up writers to focus on creating an engaging narrative. What’s more, AI-assisted content writing has opened the door to authorship for many novice writers who’s experiences would otherwise go untold. 10. Psychiatrists Artificial Intelligence (AI) has created a lot of buzz lately, but it's important to remember that no matter how complex and intelligent AI is, it currently cannot replace the sensitive rol of a psychiatrists. Psychiatrists rely on the ability to understand body language, make inferences from language and build personal relationships that allow them to truly connect with their patients. They draw connections between emotions, experiences, and backgrounds in order to deliver effective care which requires an understanding of human complexity that AI simply can't provide. For instance, a future AI may be able to diagnose depression more quickly than any human since it will have unfettered access to data on patient symptoms; however, it cannot discern the deep emotional roots of depression in the same way a psychiatrist would because AI lacks empathy due to its inability to "think" like a human. While technology can certainly supplement the work of psychiatrists, it can never replace them entirely (never being in the next few years, who really knows after that!) 11. Computer Systems Engineers + Software Developers As technology becomes more advanced, our dependence on software developers is waning as artificial intelligence takes over many of their responsibilities. AI-driven development tools are faster and more efficient, allowing projects to be completed in a fraction of the time compared to manual coding. Additionally, with AI automation, tasks like bug fixing, code optimisation, and maintenance can be left to machines. Whilst these tasks can be performed well by AI, software developers still play an important role in programming AI and training it further, making it a relatively safe role, for now. As businesses become increasingly reliant on cutting-edge technologies, it is essential for software developers to enhance AI automation, but it’s an interesting field - they’re creating something that will eventually replace themselves! 12. PR Managers Artificial Intelligence (AI) is rapidly changing the world of public relations by introducing tools to automate tedious tasks and improve workflow efficiency. AI-powered automation tools have enabled PR managers to process news items and other communications faster, develop more targeted messaging, segment audiences for tailored messages, monitor an increased quantity of customer interactions, and generate more meaningful insights from data. What this means is that with increasing speed and quality of output, AI has become indispensable in delivering results, however, it’s not taking over this role just yet: As such, public relations managers must now adjust their roles to tap into the potential of AI or risk being overtaken by competitors who embrace its power. Despite being a challenging process at first, those who manage to strengthen their understanding of this technology will stay ahead of the game. So, is your job safe from Artificial Intelligence? AI technology is becoming more and more prevalent in many industries. It's no surprise, then, that one of the primary concerns with it's growth is that it may lead to job displacement. This worry maybe a valid one but it doesn't necessarily have to be seen as a bad thing. To begin with, if you’re good at your job, use AI to make you even better! Replacing dull and monotonous tasks (like manual data entry) with AI can actually have positive benefits for human workers by creating opportunities for higher-level roles requiring creativity and thought. We’ve already seen that AI in it’s current form needs a human driver, so familiarising yourself with AI tools to help you do your job even better will make you an invaluable asset to any team. In addition, research has shown that when AI is used in certain sectors of an industry, the emergence of new jobs often far exceeds those that were replaced. All this means that while there may be some initial uncertainty associated with AI technology disrupting our current way of work, the potential value generated by its use could open up amazing possibilities. It’s clear that this era of automatisation will bring new opportunities, and with proper training and guidance, businesses and employees alike can begin to reap the benefits of AI - those with a background in the technology and skills necessary to direct AI will be highly sought after. In short - don’t shy away from AI. If you do, it will replace you in many roles. Instead, embrace it and work in harmony with artificial intelligence.
Do you want our help growing your business? Ready to go? Yes, let's get started
Just a heads up, some of the links in this article may be affiliate links, meaning we may make a small commission on any sign-ups or purchases for the tools we recommend.
| 2023-07-14T00:00:00 |
2023/07/14
|
https://www.beyond.agency/blog/will-ai-take-my-job-in-2023-and-beyond
|
[
{
"date": "2023/02/09",
"position": 15,
"query": "AI labor market trends"
}
] |
AI and ML: Leading Business Growth
|
AI and ML: Leading Business Growth
|
https://professional.mit.edu
|
[] |
96% of industry professionals say that they plan to use AI simulations, such as digital twins. · 98% of companies think AI can help overcome labor market ...
|
Why it Matters
Every aspect of business and every kind of industry is being transformed by AI and ML - whether that might be improving people processes, enhancing manufacturing, elevating customer experiences, creating impactful brands, securing infrastructure or leveraging business data. The demand for senior leaders and managers with a strategic perspective, refined capabilities, and in-depth knowledge is increasing sharply. A fluency in the strategic application of AI and ML is requisite for driving business growth and personal career growth for senior professionals.
There are significant opportunities in the industry:
96% of industry professionals say that they plan to use AI simulations, such as digital twins. (Source: PwC 2022 AI Business Survey)
98% of companies think AI can help overcome labor market challenges. (Source: PwC 2022 AI Business Survey)
82% of leaders said that their employees believe that working with AI technologies will enhance their performance and job satisfaction. (Source: State of AI in the Enterprise Fifth Edition 2022)
With this live online program, you will be transformed into a high-performing business leader equipped to create impactful business growth by enhancing efficiency, leading solution selection, improving implementation, and guiding risk management.
The AI and ML: Leading Business Growth is an action-learning-based live virtual program led by MIT faculty and is delivered in collaboration with Northwest Executive Education.
Contact Northwest for more information:
Email: [email protected]
Phone: +1 857-777-1255 (USA)
Northwest Education focuses on executive education and collaborates with universities to manage enrollments, payment services, technology, and participant support.
| 2023-02-09T00:00:00 |
https://professional.mit.edu/course-catalog/ai-and-ml-leading-business-growth
|
[
{
"date": "2023/02/09",
"position": 41,
"query": "AI labor market trends"
},
{
"date": "2023/02/09",
"position": 84,
"query": "AI workers"
},
{
"date": "2023/02/09",
"position": 1,
"query": "AI business leaders"
}
] |
|
Top 12 use cases of how ChatGPT will shape the HR ...
|
Top 12 use cases of how ChatGPT will shape the HR industry in 2023
|
https://peopleforce.io
|
[] |
ChatGPT could provide users with simple and powerful job descriptions within seconds. As you can see, OpenAI made the ChatGPT interface very minimalistic.
|
The future of AI is finally here. How much has been said about how this time would come, and how smart programs would produce everything for us? If you didn’t already know, such a program has already been released.
In 2022, San Francisco based AI research laboratory OpenAI launched the AI bot ChatGPT — and our lives will never be the same again.
How will ChatGPT impact the HR industry?
Automation using AI bots can radically change the life of recruiters and HR specialists. Given that ChatGPT is planned to implement new features you should try to master this bot as early as possible. Then, in the future, you will already have proven use cases, and it will be easier for you to navigate this brave new world.
As an employer who searches for trends (and we are sure that you fall into this category), we recommend that you be especially attentive to the reduction of resources spent on writing texts, document templates, summaries — anything that is not difficult but rather time-consuming. Especially if the AI bot itself can handle the task.
Speaking of the issues that ChatGPT can handle, here are some practical examples of how the AI chatbot simplifies HR.
All the use cases ChatGPT could provide for you.
How to use ChatGPT in recruiting
Job descriptions
This is the simplest case. Ask the bot to write a job description, for example, for a Senior JavaScript Developer position.
ChatGPT could provide users with simple and powerful job descriptions within seconds.
As you can see, OpenAI made the ChatGPT interface very minimalistic. ChatGPT chatbot responds with a fully-fledged description where you just need to enter data about location, salary, ongoing work schedule, etc. Otherwise, it is the same description that a recruiter would work with, but would spend a lot more time on it. With ChatGPT, it took about 10 seconds.
Interview questions
The next thing you can do is to list the interview questions for the candidate for that position.
You can ask a generative AI bot to make your questions as human as possible.
Adjust the number of questions or paragraphs you want in the request: 5, 10, 20, ChatGPT will come up with as many as you asked for.
Employee welcome letter
Another good example is asking the bot to generate a welcome letter for a newly hired candidate.
Large language models will drive your recruitment routine.
You can specify the length of the text to the bot. Here we asked it to include no more than 500 characters. In case you have a limit on the length, it's a great way to consider everything in the request at once.
What else should you use ChatGPT for in recruiting and hiring as an HR manager?
To collect resume templates and cover letters
To make a description of a company's career website
To help write ad text for job vacancies
To help conduct market research in a specific region
To summarize a candidate’s resume
Could ChatGPT help HR managers to build an employee onboarding plan?
This is a good question about onboarding new professionals; what about the specific steps of the onboarding program? Say, newbies for a tech company? Ask the bot to write an onboarding program for a software company.
The bot made by OpenAI has the ability to arrange a high-quality onboarding plan.
The language model prepares a very simple but effective onboarding guide. Of course, this is not a fully-fledged tasks chain for onboarding that we can take to work. But what if we refine the task for the bot's search engines?
Onboarding plan for HR managers
Suppose we ask it to write a chain of 15 tasks for onboarding a technical specialist to be performed by an HR manager.
The output is a working scheme covering how an ideal onboarding process should be implemented by an HR department. This scheme can be taken to work and schedule each of the assignments in the HRM systems, using workflows to automate them.
What about offboarding?
The employee exit process has many tasks that need to be considered to ensure that former colleagues are satisfied and can subsequently recommend the experience at your organization to their acquaintances. Use ChatGPT to collect, for example, questions for the exit interview.
You can use AI generated text to plan offboarding.
Given the inputs, ask the bot to generate questions that would, including different feedback from the employee, both the positive and negative aspects of working at the company.
How does ChatGPT mentor HR departments and suggest solutions?
Challenging situations can happen in an organization at any time. Let's say that an employee is dissatisfied with communication with their team or position, or perhaps their expectations of the employer do not match the real life scenario. What do you do in this case? ChatGPT can serve as a mentor, the user could ask the bot for advice.
Use AI-driven knowledge to communicate with your team and provide it with a clear and understandable message.
Use the search engine to regulate terminations, and choose the right words for competent communication on team changes, resignations, failures to pass the probation period, etc.
How ChatGPT can boost a company’s employer brand
Mission and values
Let's give the bot the task of creating a list of values for our fictional brand that we can later incorporate into our corporate culture. Let's do it creatively.
Make a list of corporate values for your career site.
Similarly, we can ask the bot to create a framework for the company's values and mission. All this affects the development of the modern employer brand.
EVP
Candidates are looking for companies with a competitive value proposition, that is, you should know ahead of time what to offer your employee as part of an ethical approach to work.
What happens when we ask to design an employee value proposition on ChatGPT?
Make an EVP for your website.
When creating an EVP you need to specify your inputs, i.e. what you want to see in the message, and what you want your team to be distinguished by. Experiment and ask the bot to add more nuance to its response.
Could ChatGPT help produce engagement surveys?
Let's dig deeper and think about what specific processes bots can help with. For example, could it help to design an engagement survey?
Let's ask it to make a questionnaire or a feedback form to assess the level of employee engagement.
Use OpenAI bot to receive employee feedback.
At our request, the bot gave us 20 ready-made questions that you can upload to your HRM system tools and conduct a fully-fledged survey for users.
But let's say we want to consult with the ChatGPT bot about what kind of surveys are rational to conduct at the company in general.
Ask ChatGPT to name your most valuable surveys to collect more feedback.
Now take a look down the list and see if you're doing all the surveys yourself at your company, or if you're missing something. Either way, know that ChatGPT will help you create any of those listed.
How ChatGPT handles different descriptions and templates for Human Resource Management tasks
Often we just need help in describing various details of an HR routine. ChatGPT is sent to us by fate here because it copes with descriptions perfectly.
What exactly can we describe?
Competency descriptions for the Performance Review method
Competency descriptions for the Performance Review method
Letter templates for different types of communication either with candidates or employees
for different types of communication either with candidates or employees Description of objectives and key results , as well as employee KPIs
, as well as employee Templates for discussing various topics in 1-on-1 meetings
Summaries of 1-on-1 meetings
of 1-on-1 meetings Templates for employee development plans
Ask ChatGPT to search for the world's best examples of development plans.
Does the ChatGPT search engine have disadvantages?
OpenAI CEO Sam Altman himself is rather cautious about the program's future: 'I do think there's a change that will probably come at some point — but not as dramatically as people think in the short term', he said in a recent interview.
One thing to keep in mind is that the bot's knowledge is not limitless. OpenAI demonstrates the capabilities of the GPT-3.5 platform, which owned the database up until 2021. Accordingly, the bot does not possess information that came later, neither about current events, nor about new trends. This includes recent developments and improvements that can be applied to HR work.
Will ChatGPT replace your HR department?
This question is akin to the eternal "can a robot turn a canvas into a beautiful masterpiece"... although wait, ChatGPT is already close to that, because it already writes lyrics.
Okay then, you have our word that in Human Relations, no machine learning or artificial intelligence can yet replace a quality specialist. We need experts who will make the challenges of our time as easy as possible for team members, as well as open and engaging. This AI bot can't do that yet, but no one said HR professionals can't enjoy the power of automation in the interim.
In the future, a new version of ChatGPT technology really has the potential to impact the labor market and lead to the automation of many processes.
| 2023-02-09T00:00:00 |
https://peopleforce.io/blog/12-use-cases-of-how-chatgpt-will-shape-the-hr-industry
|
[
{
"date": "2023/02/09",
"position": 32,
"query": "ChatGPT employment impact"
}
] |
|
How OpenAI, ChatGPT Fuel Data Labeling Work and ...
|
How OpenAI, ChatGPT Fuel Data Labeling Work and Economic Impact
|
https://cloudwars.com
|
[
"Kieron Allen"
] |
02:06 — Kieron notes the increase in demand for data labelers makes way for new talent in the AI/ML space and will have an economic impact on other countries.
|
In episode 50 of the Acceleration Economy Minute, Kieron Allen explains how OpenAI, the developer of ChatGPT, has hired a significant number of contractors to conduct data labeling.
This episode of the Acceleration Economy Minute is sponsored by Acceleration Economy’s Digital CIO Summit, taking place April 4-6. Register for the free event here. Tune in to the event to hear from CIO practitioners discuss their modernization and growth strategies.
Highlights
00:34 — OpenAI, the company behind ChatGPT, has ramped up hiring around the world. The company has brought in nearly 1,000 remote contractors over the past six months. About 60% of these contractors have been tasked with conducting data labeling.
01:15 — Within artificial intelligence (AI) and machine learning (ML), data labeling is the process of identifying raw data. Once the data is identified, the process includes adding context, meaningful information, and labels to this data so that ML systems can learn more quickly, which is crucial in the development of generative AI.
02:06 — Kieron notes the increase in demand for data labelers makes way for new talent in the AI/ML space and will have an economic impact on other countries.
Which companies are the most important vendors in AI and Hyperautomation? Click here to see the Acceleration Economy Top 10 AI/Hyperautomation Short List, as selected by our expert team of practitioner-analysts
| 2023-02-09T00:00:00 |
2023/02/09
|
https://cloudwars.com/acceleration-economy-minute/how-openai-chatgpt-fuel-data-labeling-work-and-economic-impact/
|
[
{
"date": "2023/02/09",
"position": 55,
"query": "ChatGPT employment impact"
}
] |
Using ChatGPT in recruitment: What does the future hold?
|
Using ChatGPT in recruitment: What does the future hold?
|
https://jobadder.com
|
[
"Martin Herbst Is The Ceo Of Jobadder. He Has More Than Years Of Experience As A Tech Leader",
"Is Adept At Launching",
"Scaling",
"Leading Saas Companies Strength To Strength."
] |
“I've tested and researched ChatGPT and it's going to do incredible things to some parts of the recruitment job that are tedious, laborious, time-consuming and ...
|
Recruitment Blog Using ChatGPT in recruitment: What does the future hold? Martin Herbst Martin Herbst is the CEO of JobAdder. He has more than 20 years of experience as a tech leader, and is adept at launching, scaling, and leading SaaS companies from strength to strength.
Everyone is chatting about ChatGPT at the moment (sorry for the pun, I had to!) so I thought I’d explore how to use ChatGPT in recruitment and what it means for the industry.
First off, it’s important to note that the recruitment industry will continue to evolve as it has in the past, which means we’ll see more and more attention on automation.
With the cooling of the market in 2023, recruiters are going to have more time to breathe and focus on business development. This will allow them to think about their pipeline longer term and take a hard look at where they’re focusing and how they’re diversifying to deal with the softening of the market.
I always say this but it’s so important to tool up. This is your time to get more efficient. If you’re running super fast throughout 2022 and things are slowing down, make sure that you’re training up your team, utilising your tech stack in the best possible way and continuing to invest in learning and development.
The party’s not over but things have got to get a little bit leaner. I think that’s the evolution and I do get really passionate about how tech can play a role (as you’d expect!).
Automation is going to continue to be a bigger and bigger trend. The reason why ChatGPT is such a topic right now is probably because it’s the most usable, tangible and real-life example since Siri was introduced of artificial intelligence (AI).
To get into some basics of ChatGPT…
What does ChatGPT stand for?
It’s a generative pre-trained transformer, so essentially it’s just a set of deep-learning algorithms. What sets it apart is that it’s actually reinforced by human feedback, that’s why it works so well.
OpenAI, the makers of ChatGPT, explain it like so: “We’ve trained a model called ChatGPT which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer follow-up questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests.”
How to use ChatGPT in recruitment
Tech is only good if it’s actually helping humans. It shouldn’t be a crutch and it won’t replace recruitment. It won’t replace completely how you do job orders or job descriptions, but it can help a lot.
It allows you to go faster and it allows you to be a bit smarter. It doesn’t mean that you should be releasing ownership of the actual recruitment process, it just means you can improve the process.
It’s not a crutch, it’s an accelerator.
In our recent webinar exploring global recruitment trends, I discussed this topic with JobAdder’s recruitment advisor Greg Savage and he said that he’s taken a crash course in ChatGPT to understand its potential impact on the recruitment sector.
“I’ve tested and researched ChatGPT and it’s going to do incredible things to some parts of the recruitment job that are tedious, laborious, time-consuming and not done very well by recruiters. For example, ChatGPT can look through a job spec and come up with 10 questions you should ask, ChatGPT can write a job ad for you, it can write a resume for you and much more. That’s going to be fantastic.”
While these benefits are exciting, Greg did warn that it could hurt some recruiters. “The recruiters it’s going to hurt are those who are totally transactional and spend all their time on those activities and that’s the only value they bring. For the recruiters who have strong influencing skills and who can create outcomes, ChatGPT doesn’t do that.”
As with any piece of tech, ChatGPT can be used by recruiters to power what they do, streamline their processes and free up time to focus on tasks that add value.
To help with this, we’ve created an integration with ChatGPT through Zapier so you can actually use JobAdder to hook up to ChatGPT to help you write the job ad very quickly.
This gives you a good foundation for the job ad, which you can then tweak to ensure it reflects the specifics and uniqueness of that role.
If you’d like to learn more about ChatGPT, how it integrates with JobAdder or just about the general cool tools that the JobAdder ATS and CRM offers, please contact our friendly team.
Related blog posts Recruitment blog Crafting exceptional candidate experiences through data analytics To excel in the competition for top talent, proactive workforce planning is essential. Traditional methods struggle to adapt to evolving … Read more Cold calling is dead: How marketing can resurrect your sales strategy The art of cold calling has been around for decades, and has served many recruiters well over the years. However, … Read more Data culture matters for your agency to succeed Did you know that data-driven companies are 23 times more likely to beat their competitors and 19 times more likely … Read more There are no results to display. Please try a different keyword or reset the filters to see everything.
| 2023-02-09T00:00:00 |
https://jobadder.com/gb/blog/chatgpt-recruitment/
|
[
{
"date": "2023/02/09",
"position": 65,
"query": "ChatGPT employment impact"
}
] |
|
Legitimate Labor Organizations
|
Legitimate Labor Organizations
|
https://laborlaw.ph
|
[
"Labor Law Ph"
] |
Legitimate labor organizations refer to labor organizations that registered with the Department of Labor and Employment (DOLE).
|
Legitimate labor organizations refer to labor organizations that registered with the Department of Labor and Employment (DOLE).
“Legitimate Labor Organization” – refers to any labor organization in the private sector
registered or reported with the Department in accordance with Rules III and IV of [DOLE Department Order No. 40-03]. (Section 1[ff], Rule I, DOLE Department Order No. 40, Series of 2003, as amended by A-I)
The concepts of a union and of a legitimate labor organization are different from, but related to, the concept of a bargaining unit. (Holy Child Catholic School v. Sto. Tomas, En Banc, G.R. No. 179146, 23 July 2013)
Article 212(g) of the Labor Code defines a labor organization as “any union or association of employees which exists in whole or in part for the purpose of collective bargaining or of dealing with employers concerning terms and conditions of employment.” Upon compliance with all the documentary requirements, the Regional Office or Bureau shall issue in favor of the applicant labor organization a certificate indicating that it is included in the roster of legitimate labor organizations. Any applicant labor organization shall acquire legal personality and shall be entitled to the rights and privileges granted by law to legitimate labor organizations upon issuance of the certificate of registration. (Sta. Lucia East Commercial Corporation, v. Secretary of Labor and Employment, G.R. No. 162355, August 14, 2009)
On the other hand, a bargaining unit has been defined as a “group of employees of a given employer, comprised of all or less than all of the entire body of employees, which the collective interests of all the employees, consistent with equity to the employer, indicated to be best suited to serve reciprocal rights and duties of the parties under the collective bargaining provisions of the law.” (Holy Child Catholic School v. Sto. Tomas, supra.)
A bargaining unit is a group of employees sought to be represented by a petitioning union. Such employees need not be members of a union seeking the conduct of a certification election. A union certified as an exclusive bargaining agent represents not only its members but also other employees who are not union members. (Ibid.)
A federation, national union or industry or trade union center or an independent union shall acquire legal personality and shall be entitled to the rights and privileges granted by law to legitimate labor organizations upon issuance of the certificate of registration based on the following requirements:
1) Fifty pesos (P50.00) registration fee;
2) The names of its officers, their addresses, the principal address of the labor organization, the minutes of the organizational meetings and the list of the workers who participated in such meetings;
3) In case the applicant is an independent union, the names of all its members comprising at least twenty percent (20%) of all the employees in the bargaining unit where it seeks to operate;
4) If the applicant union has been in existence for one or more years, copies of its annual financial reports; and,
5) Four copies of the constitution and by-laws of the applicant union, minutes of its adoption or ratification, and the list of the members who participated in it. (Article 240, P.D. 442, Labor Code)
A duly registered federation or national union may directly create a local chapter by issuing a charter certificate indicating the establishment of the local chapter. (Article 241, Ibid.)
To create a local chapter and register it, there is no 20% registration requirement – i.e. the requirement that membership should at least be 20% of the bargaining unit is not applicable to a local chapter.
The chapter shall acquire legal personality only for purposes of filing a petition for certification election from the date it was issued a charter certificate. (Article 241, Ibid.)
The chapter shall be entitled to all other rights and privileges of a legitimate labor organization only upon the submission of the following documents in addition to its charter certificate:
1) The names of the chapter’s officers, their addresses, and the principal office of the chapter; and
2) The chapter’s constitution and by-laws: Provided, That where the chapter’s constitution and by-laws are the same as that of the federation or the national union, this fact shall be indicated accordingly. (Paragraph 2, Article 241, Ibid.)
The additional supporting requirements shall be certified under oath by the secretary or treasurer of the chapter and attested by its president. (Paragraph 3, Article 241, Ibid.)
The Bureau shall act on all applications for registration within thirty (30) days from filing.
All requisite documents and papers shall be certified under oath by the secretary or the treasurer of the organization, as the case may be, and attested to by its president. (Article 242, Ibid.)
The decision of the Labor Relations Division in the regional office denying registration may be appealed by the applicant union to the Bureau within ten (10) days from receipt of notice thereof. (Article 243, Ibid.)
Subject to Article 238,185 if the applicant for registration is a federation or a national union, it shall, in addition to the requirements of the preceding Articles, submit the following:
1) Proof of the affiliation of at least ten (10) locals or chapters, each of which must be a duly recognized collective bargaining agent in the establishment or industry in which it operates, supporting the registration of such applicant federation or national union; and,
2) The names and addresses of the companies where the locals or chapters operate and the list of all the members in each company involved. (Article 244, Ibid.)
The certificate of registration of any legitimate labor organization, whether national or local, may be cancelled by the Bureau, after due hearing, only on the grounds specified in Article 239 hereof. (Article 245, Ibid.)
A petition for cancellation of union registration shall not suspend the proceedings for certification election nor shall it prevent the filing of a petition for certification election.
In case of cancellation, nothing herein shall restrict the right of the union to seek just and equitable remedies in the appropriate courts. (Article 246, Ibid.)
The following may constitute grounds for cancellation of union registration:
1) Misrepresentation, false statement or fraud in connection with the adoption or ratification of the constitution and by-laws or amendments thereto, the minutes of ratification, and the list of members who took part in the ratification;
2) Misrepresentation, false statements or fraud in connection with the election of officers, minutes of the election of officers, and the list of voters;
3) Voluntary dissolution by the members. (Article 247, Ibid.)
The registration of a legitimate labor organization may be cancelled by the organization itself: Provided, That at least two-thirds of its general membership votes, in a meeting duly called for that purpose to dissolve the organization: Provided, further, That an application to cancel registration is thereafter submitted by the board of the organization, attested to by the president thereof. (Article 248, Ibid.)
All existing federations and national unions which meet the qualifications of a legitimate labor organization and none of the grounds for cancellation shall continue to maintain their existing affiliates regardless of the nature of the industry and the location of the affiliates. (Article 249, Ibid.)
A legitimate labor organization shall have the right:
1) To act as the representative of its members for the purpose of collective bargaining;
2) To be certified as the exclusive representative of all the employees in an appropriate bargaining unit for purposes of collective bargaining;
3) To be furnished by the employer, upon written request, with its annual audited financial statements, including the balance sheet and the profit and loss statement, within thirty (30) calendar days from the date of receipt of the request, after the union has been duly recognized by the employer or certified as the sole and exclusive bargaining representative of the employees in the bargaining unit, or within sixty (60) calendar days before the expiration of the existing collective bargaining agreement, or during the collective bargaining negotiation;
4) To own property, real or personal, for the use and benefit of the labor organization and its members;
5) To sue and be sued in its registered name; and,
6) To undertake all other activities designed to benefit the organization and its members, including cooperative, housing, welfare and other projects not contrary to law.
Notwithstanding any provision of a general or special law to the contrary, the income and the properties of legitimate labor organizations, including grants, endowments, gifts, donations and contributions they may receive from fraternal and similar organizations, local or foreign, which are actually, directly and exclusively used for their lawful purposes, shall be free from taxes, duties and other assessments. The exemptions provided herein may be withdrawn only by a special law expressly repealing this provision. (Article 251, P.D. 442, Labor Code)
The following are documents required to be submitted to the Bureau by the legitimate labor organization concerned:
1) Its constitution and by-laws, or amendments thereto, the minutes of ratification, and the list of members who took part in the ratification of the constitution and by-laws within thirty (30) days from adoption or ratification of the constitution and by-laws or amendments thereto;
2) Its list of officers, minutes of the election of officers, and list of voters within thirty (30) days from election;
3) Its annual financial report within thirty (30) days after the close of every fiscal year; and,
4) Its list of members at least once a year or whenever required by the Bureau of Labor Relations. (Article 252, Ibid.)
Failure to comply with the above requirements shall not be a ground for cancellation of union registration but shall subject the erring officers or members to suspension, expulsion from membership, or any appropriate penalty. (Paragraph 2, Article 252, Ibid.)
“Affiliate” – refers to an independent union affiliated with a federation, national union or a chartered local which was subsequently granted independent registration but did not disaffiliate from its federation, reported to the Regional Office and the Bureau in accordance with Rule III, Sections 6 and 7 of [DOLE Department Order No. 40-03]. (Section 1[b], Rule I, DOLE Department Order No. 40, Series of 2003, as amended by A-I)
The purpose of affiliation by a local union with a mother union or a federation “is to increase by collective action the bargaining power in respect of the terms and conditions of labor. Yet the locals remained the basic units of association, free to serve their own and the common interest of all, subject to the restraints imposed by the Constitution and By-Laws of the Association, and free also to renounce the affiliation for mutual welfare upon the terms laid down in the agreement which brought it into existence.” (MSMG-UWP v. Ramos, G.R. No. 113907, 28 February 2000)
The report of affiliation of independently registered labor unions with a federation or national union shall be accompanied by the following documents:
1) resolution of the labor union’s board of directors approving the affiliation;
2) minutes of the general membership meeting approving the affiliation;
3) the total number of members comprising the labor union and the names of members
who approved the affiliation;
4) the certificate of affiliation issued by the federation in favor of the independently registered labor union; and
5) written notice to the employer concerned if the affiliating union is the incumbent bargaining agent. (Section 7, Rule III, Ibid.)
A local union does not owe its existence to the federation with which it is affiliated. It is a separate and distinct voluntary association owing its creation to the will of its members. Mere affiliation does not divest the local union of its own personality, neither does it give the mother federation the license to act independently of the local union. It only gives rise to a contract of agency, where the former acts in representation of the latter. Hence, local unions are considered principals while the federation is deemed to be merely their agent. As such principals, the unions are entitled to exercise the rights and privileges of a legitimate labor organization, including the right to seek certification as the sole and exclusive bargaining agent in the appropriate employer unit. (Coastal Subic Bay Terminal, Inc. v. DOLE-Office of the Secretary, G.R. No. 157117, 20 November 2006)
FILIPINO PIPE AND FOUNDRY CORPORATION v. NLRC, G.R. No. 115180, 16 November 1999
⦁ [D]irect and primary responsibility for the damages allegedly caused by the illegal strike sued upon fall on the local union FPWU, being the principal, and not on respondent NLU-TUCP, a mere agent of FPWU-NLU which assisted the latter in filing the notice of strike. Being just an agent, the notice of strike filed by Atty. Eulogio Lerum, the national president of NLU-TUCP, is deemed to have been filed by its principal, the FPWU-NLU. Having thus dismissed the claim for damages against the principal, FPWU-NLU, the action for damages against its agent, respondent NLU-TUCP, and Atty. Lerum, has no more leg to stand on and should also be dismissed.
A local union has the right to disaffiliate from its mother union or declare its autonomy. A local union, being a separate and voluntary association, is free to serve the interests of all its members including the freedom to disaffiliate or declare its autonomy from the federation to which it belongs when circumstances warrant, in accordance with the constitutional guarantee of freedom of association. (MSMG-UWP v. Ramos, G.R. No. 113907, 28 February 2000)
[A] local union which has affiliated itself with a federation is free to sever such affiliation anytime and such disaffiliation cannot be considered disloyalty. In the absence of specific provisions in the federations constitution prohibiting disaffiliation or the declaration of autonomy of a local union, a local may dissociate with its parent union. (Ibid.)
[L]abor unions may disaffiliate from their mother federations to form a local or independent union only during the 60-day freedom period immediately preceding the expiration of the CBA… However, such disaffiliation must be effected by a majority of the members in the bargaining unit. (National Union of Bank Employees [NUBE] v. Philnabank Employees Association[PEMA], G.R. No. 174287, 12 August 2013)
[T]he right of the local members to withdraw from the federation and to form a new local union depends upon the provisions of the union’s constitution, by-laws and charter and, in the absence of enforceable provisions in the federation’s constitution preventing disaffiliation of a local union, a local may sever its relationship with its parent. (Coastal Subic Bay Terminal, Inc. v. DOLE-Office of the Secretary, supra.)
[T]he right of the local members to withdraw from the federation and to form a new local union depends upon the provisions of the union’s constitution, by-laws and charter and, in the absence of enforceable provisions in the federation’s constitution preventing disaffiliation of a local union, a local may sever its relationship with its parent. (National Union of Bank Employees [NUBE] v. Philnabank Employees Association[PEMA], supra.)
NATIONAL UNION OF BANK EMPLOYEES [NUBE] v. PHILNABANK EMPLOYEES ASSOCIATION [PEMA], G.R. No. 174287, 12 August 2013
⦁ [T]here is no merit on NUBE’s contention that PEMA’s disaffiliation is invalid for non-observance of the procedure that union members should make such determination through secret ballot and after due deliberation, conformably with Article 241 (d) of the Labor Code, as amended.38 Conspicuously, other than citing the opinion of a “recognized labor law authority,” NUBE failed to quote a specific provision of the law or rule mandating that a local union’s disaffiliation from a federation must comply with Article 241 (d) in order to be valid and effective.
⦁ Granting, for argument’s sake, that Article 241 (d) is applicable, still, We uphold PEMA’s disaffiliation from NUBE. First, non-compliance with the procedure on disaffiliation, being premised on purely technical grounds cannot rise above the employees’ fundamental right to self-organization and to form and join labor organizations of their own choosing for the purpose of collective bargaining.39 Second, the Article nonetheless provides that when the nature of the organization renders such secret ballot impractical, the union officers may make the decision in behalf of the general membership. In this case, NUBE did not even dare to contest PEMA’s representation that “PNB employees, from where [PEMA] [derives] its membership, are scattered from Aparri to Jolo, manning more than 300 branches in various towns and cities of the country,” hence, “[to] gather the general membership of the union in a general membership to vote through secret balloting is virtually impossible.”40 It is understandable, therefore, why PEMA’s board of directors merely opted to submit for ratification of the majority their resolution to disaffiliate from NUBE. Third, and most importantly, NUBE did not dispute the existence of the persons or their due execution of the document showing their unequivocal support for the disaffiliation of PEMA from NUBE. Note must be taken of the fact that the list of PEMA members (identifying themselves as “PEMA-Serrana Group”41) who agreed with the board resolution was attached as Annex “H” of PEMA’s petition before the CA and covered pages 115 to 440 of the CA rollo. While fully displaying the employees’ printed name, identification number, branch, position, and signature, the list was left unchallenged by NUBE. No evidence was presented that the union members’ ratification was obtained by mistake or through fraud, force or intimidation. Surely, this is not a case where one or two members of the local union decided to disaffiliate from the mother federation, but one where more than a majority of the local union members decided to disaffiliate.
⦁ Consequently, by PEMA’s valid disaffiliation from NUBE, the vinculum that previously bound the two entities was completely severed. As NUBE was divested of any and all power to act in representation of PEMA, any act performed by the former that affects the interests and affairs of the latter, including the supposed expulsion of Serrana et al., is rendered without force and effect.
⦁ Also, in effect, NUBE loses it right to collect all union dues held in its trust by PNB. The moment that PEMA separated from and left NUBE and exists as an independent labor organization with a certificate of registration, the former is no longer obliged to pay dues and assessments to the latter; naturally, there would be no longer any reason or occasion for PNB to continue making deductions…
VOLKSCHEL LABOR UNION v. BUREAU OF LABOR RELATIONS, G.R. No. L-45824, 19 June 1985
⦁ In other words, [Federation/National Union] ALUMETAL is entitled to receive the dues from respondent companies as long as petitioner union is affiliated with it and respondent companies are authorized by their employees (members of petitioner union) to deduct union dues. Without said affiliation, the employer has no link to the mother union. The obligation of an employee to pay union dues is coterminous with his affiliation or membership. “The employees’ check-off authorization, even if declared irrevocable, is good only as long as they remain members of the union concerned.” A contract between an employer and the parent organization as bargaining agent for the employees is terminated by the disaffiliation of the local of which the employees are members. Respondent companies therefore were wrong in continuing the check-off in favor of respondent federation since they were duly notified of the disaffiliation and of petitioner’s members having already rescinded their check-off authorization.
⦁ Book V, Presidential Decree No. 442, a.k.a. Labor Code of the Philippines
⦁ Book V, Omnibus Rules Implementing the Labor Code
⦁ DOLE Department Order No. 40, Series of 2003
⦁ DOLE Department Order No. 40-A-I, Series of 2003
⦁ DOLE Department Order No. 40-B, Series of 2003
⦁ DOLE Department Order No. 40-C, Series of 2004
⦁ DOLE Department Order No. 40-D, Series of 2005
⦁ DOLE Department Order No. 40-F-3, Series of 2008
⦁ DOLE Department Order No. 40-G-03, Series of 2010
⦁ DOLE Department Order No. 40-I, Series of 2015
⦁ DOLE Department Order No. 15, Series of 2015
—
/Updated: February 9, 2023
| 2022-05-29T00:00:00 |
2022/05/29
|
https://laborlaw.ph/legitimate-labor-organizations/
|
[
{
"date": "2023/02/09",
"position": 14,
"query": "AI labor union"
}
] |
Is AI software a partner for journalism, or a disaster?
|
Is AI software a partner for journalism, or a disaster?
|
https://www.cjr.org
|
[] |
... Union speech in the style of various historical figures, including Shakespeare, Aristotle, and Mahatma Gandhi. Cleopatra: “Let us continue to work together ...
|
Sign up for The Media Today, CJR’s daily newsletter.
In November, OpenAI, a company that develops artificial-intelligence software, released ChatGPT, a program that allows users to ask conversational-style questions and receive essay-style answers. It soon became clear that, unlike with some earlier chat-software programs, this one could, in a matter of seconds, generate content that was both readable and reasonably intelligent. Unsurprisingly, this caused consternation among humans who get paid to generate content that is readable and intelligent. And their concerns are reasonable: companies that make money creating such content may well see AI-powered tools as an opportunity to cut costs and increase profits, two things that companies that make money from content like to do.
AI in the media is, more broadly, having a moment. Around the same time that ChatGPT launched, CNET, a technology news site, quietly started publishing articles that were written with the help of artificial intelligence, as Futurism reported last month. A disclaimer on the site assured readers that all of the articles were checked by human editors, but as Futurism later reported, many of the CNET pieces written by the AI software not only contained errors, but in some cases were plagiarized. After these reports came out, Red Ventures—a private-equity firm that owns CNET and a number of other online publications, including Lonely Planet and Healthline—told staff that it was pausing the use of the AI software, which it said had been developed in-house.
ICYMI: Journalists Remain on Twitter, but Tweet Slightly Less
As CNET pressed pause, media companies announced plans to expand their use of AI. The Arena Group, which publishes Sports Illustrated among other magazines, is now using AI to generate articles and story ideas, according to the Wall Street Journal; Arena said that it doesn’t plan to replace journalists with AI, but to “support content workflows, video creation, newsletters, sponsored content and marketing campaigns,” according to Ross Levinsohn, the CEO and a former publisher of the Los Angeles Times. BuzzFeed, meanwhile, said that it plans to use OpenAI’s software to develop quizzes and personalize content for readers. After that news broke, BuzzFeed‘s stock more than doubled in price, a move “reminiscent of the crypto and blockchain craze five years ago when shares of a company would surge when it announced a potential partnership or entry into the popular sector,” Bloomberg’s Alicia Diaz and Gerry Smith wrote. Jonah Peretti, BuzzFeed’s CEO, told staff that the use of AI was not about “workplace reduction,” according to a spokesperson quoted by the Journal. (The Journal also reported that BuzzFeed “remains focused on human-generated journalism” in its newsroom.)
The use of AI software to create journalism didn’t begin with the rise of ChatGPT. The Associated Press has been using AI to write corporate earnings reports since 2015, since such reports are often so formulaic that they don’t require human input. (Incidentally, the AP also recently asked ChatGPT to write the president’s State of the Union speech in the style of various historical figures, including Shakespeare, Aristotle, and Mahatma Gandhi. Cleopatra: “Let us continue to work together, to strive for a better future, and to build a stronger, more prosperous Egypt.”) And Yahoo and several other content publishers have been using similar AI-powered tools for several years, to generate game summaries and corporate reports.
While the practice may not be as new as some of the commentary around it may have you believe, however, the popularity of ChatGPT, and the quality of its output, has led to a renewed debate about its potential impact on journalism. Jack Shafer, a media columnist at Politico, is relatively sanguine about the possibilities of AI-powered content software to improve their work. Journalism “doesn’t exist to give reporters and editors a paycheck,” Shafer wrote. “It exists to serve readers. If AI helps newsrooms better serve readers, they should welcome its arrival.” This will be difficult if the technology does also lead to widespread job losses, however. Max Read, a former editor at Gawker, wrote recently in his newsletter that “any story you hear about using AI is [fundamentally] a story about labor automation,” whether that involves adding tools that could help journalists do more with less or replacing humans completely.
Sign up for CJR’s daily email
Both paths, Read wrote, “suck, in my opinion.” Indeed, those who fear the ChatGPTization of journalism don’t see the problem merely as one of labor rights. Kevin Roose, of the New York Times, described AI-generated content as “pink slime” journalism on a recent episode of the Hard Fork podcast with Casey Newton, using a term that more often refers to low-quality meat products. The term “pink slime” has been used to describe low-quality journalism before, as Priyanjana Bengani has documented exhaustively for CJR; by using it to refer to AI-powered content, Roose and others seem to mean journalism that simulates human-created content without offering the real thing.
Experts, meanwhile, have said that the biggest flaw in a “large language model” like ChatGPT is that, while it is capable of mimicking human writing, it has no real understanding of what it is writing about, and so it frequently inserts errors and flights of fancy that some have referred to as “hallucinations.” Colin Fraser, a data scientist at Meta, has written that the central quality of this type of model is that “they are incurable, constant, shameless bullshitters. Every single one of them. It’s a feature, not a bug.” Gary Marcus, a professor of psychology and neuroscience at New York University, has likened this kind of software to “a giant autocomplete machine.”
Newton wrote in a recent edition of his Platformer newsletter that some of the functions for which ChatGPT and similar software will be used probably aren’t worth journalists worrying about. “If you run a men’s health site, there are only so many ways to tell your readers to eat right and get regular exercise,” Newton said. He wrote in a different edition of the newsletter, however, that these software engines could also potentially be used to generate reams of plausible-sounding misinformation. Dave Karpf, a professor of internet politics at George Washington University, wrote that the furor over ChatGPT reminds him of the hysteria around “content farms” in 2009 and 2010, when various companies paid writers tiny sums of money to generate content based on popular search terms, then monetized those articles through ads. As Karpf notes, the phenomenon appeared to spell disaster for journalism, but it was ultimately short-circuited when Google changed its search algorithm to downrank “low quality” content. (“Relying on platform monopolists to protect the public interest isn’t a great way to run a civilization,” Karpf wrote, “but it’s better than nothing.”)
Unfortunately, in this case, Google isn’t casting a skeptical eye toward AI-generated content—it is planning to get into the business itself; this week, it unveiled a new chat-based model called “Bard.” (Shakespeare obviously wasn’t busy enough writing the State of the Union.) Nor is it just Google: Microsoft is also getting into the AI software game, having recently invested ten billion dollars for a stake in OpenAI, the ChatGPT creator. This raises the possibility that search engines—which already provide answers to simple questions, such as What is the score in the Maple Leafs game?—could offer more sophisticated content without having to link to anything, potentially weakening online publishers that are already struggling. Then again, Bard made a mistake in its trial demo.
While there are some obvious reasons to be concerned about the impact of AI software on journalism, it seems a little early to say definitively whether it is bad or good. ChatGPT seems to agree: When I asked it to describe its impact on the media industry recently, it both-sidesed the question in fine journalistic style. “ChatGPT has the potential to impact the media industry in a number of ways [because] it can generate human-like text, potentially reducing the need for human writers,” it wrote. “But it may also lead to job loss and ethical concerns.”
Other notable stories:
Yesterday, Evan Lambert, a reporter for the TV network NewsNation, was told to stop broadcasting, then arrested, during a press conference by Mike DeWine, the governor of Ohio. Lambert was charged with criminal trespassing and disorderly conduct, according to the Washington Post; it’s not entirely clear what led to Lambert being detained, the Post reports, but video footage of the incident appeared to show him complying with the order to stop filming. A spokesperson for DeWine said that the governor had been told that Lambert was ordered to stop because “the volume of his reporting was perceived to be interfering with the event,” a rationale from which DeWine firmly distanced himself.
Also yesterday, the House Oversight Committee grilled former executives from Twitter on the platform’s suppression of a New York Post story about Hunter Biden’s laptop prior to the 2020 election. The executives conceded that their handling of the story was a mistake, but flatly denied Republican claims of collusion with the FBI or Joe Biden’s presidential campaign. And in other ways, CNN’s Oliver Darcy writes, the hearing “backfired in spectacular fashion” for the GOP—airing claims that Twitter accommodated Trump and that Trump himself made censorious requests of the company.
According to New York’s Andrew Rice, James O’Keefe, the founder and guiding light of the right-wing sting group Project Veritas, has gone on paid leave and could be ousted as the group’s leader by its board, which is set to meet tomorrow. O’Keefe’s future with the group “has become uncertain amid reports of internal turmoil, lawsuits from former employees, leaks about its internal workings, and a federal investigation into its conduct in purchasing a diary stolen from Ashley Biden, the president’s daughter,” Rice reports.
In 2021, Ozy, a media company, collapsed after Ben Smith, then the media columnist at the New York Times, raised serious concerns about its business practices. Max Tani reports for Semafor (where Smith is now the editor in chief) that Ozy is now seeking a comeback: Carlos Watson, Ozy’s founder, pitched potential advertisers and investors in New York yesterday, without mentioning the company’s “extremely public implosion.”
And Senator Mitt Romney gave McKay Coppins, a writer at The Atlantic, access to reams of his private correspondence for a book that Coppins is writing about Romney, Axios’s Mike Allen reports. The volume of material “is unheard of for a major sitting officeholder” to give away, Allen writes: “a trove historians dream of but rarely get.”
ICYMI: Rewire News Group’s editors on abortion coverage, Supreme Court reporters, and TikTok
| 2023-02-09T00:00:00 |
https://www.cjr.org/the_media_today/ai_software_chatgpt_journalism.php
|
[
{
"date": "2023/02/09",
"position": 83,
"query": "AI labor union"
},
{
"date": "2023/02/09",
"position": 6,
"query": "AI journalism"
}
] |
|
Striking Workers Should Receive Unemployment Benefits
|
Testimony: Striking Workers Should Receive Unemployment Benefits
|
https://tcf.org
|
[
"Michele Evermore",
"Former Interim Director Of Disability Economic Justice",
"Senior Fellow"
] |
First, alleviating individual suffering when claimants lose work through no fault of their own is clear—when a worker's union ... Can AI improve America's ...
|
Michele Evermore is the interim director of disability economic justice and senior fellow at The Century Foundation, where she focuses on policy for improving the nation’ social insurance programs.
| 2023-02-09T00:00:00 |
2023/02/09
|
https://tcf.org/content/testimony/testimony-striking-workers-should-receive-unemployment-benefits/
|
[
{
"date": "2023/02/09",
"position": 92,
"query": "AI labor union"
}
] |
Educating in a World of Artificial Intelligence
|
Educating in a World of Artificial Intelligence
|
https://www.gse.harvard.edu
|
[] |
Chris Dede discusses how education can evolve to work with — rather than fight against — artificial intelligence.
|
Senior Researcher Chris Dede isn't overly worried about growing concerns over generative artificial intelligence, like ChatGPT, in education. As a longtime researcher on emerging technologies, he's seen many decades where new technologies promised to upend the field. Instead, Dede says artificial intelligence requires educators to get smarter about how they teach in order to truly take advantage of what AI has to offer.“The trick about AI is that to get it, we need to change what we're educating people for because if you educate people for what AI does well, you're just preparing them to lose to AI. But if you educate them for what AI can't do, then you've got IA [Intelligence Augmentation],” he says. Dede, the associate director of research for the National AI Institute for Adult Learning and Online Education, says AI raises the bar and it has the power to significantly impact learning in powerful ways.
In this episode of the Harvard EdCast, Dede talks about how the field of education needs to evolve and get smarter, in order to work with — not against — artificial intelligence.
ADDITIONAL RESOURCES
TRANSCRIPT
Jill Anderson: I'm Jill Anderson. This is the Harvard EdCast.
Chris Dede thinks we need to get smarter about using artificial intelligence and education. He has spent decades exploring emerging learning technologies as a Harvard researcher. The recent explosion of generative AI, like ChatGPT, has been met with mixed reactions in education. Some public school districts have banned it. Some colleges and universities have tweaked their teaching and learning already.
Generative AI raises que
Chris Dede: I've actually been working with AI for more than half a century. Way back when when I was a graduate student, I read the first article on AI in education, which was published in 1970. And the author confidently predicted that we wouldn't need teachers within five or six years because AI was going to do everything. And of course, we still see predictions like that today.
But having lived through nine hype cycles for AI, I'm both impressed by how much it's advanced, but I'm also wary about elaborate claims for it. And there is a lot of excitement now about generative AI is the term that people are using, which includes programs like ChatGPT. It includes things like Dolly that are capable of creating images. It includes really AI on its own doing performances that we previously would have thought were something that people would have to do.
But it's interesting to compare ChatGPT to a search engine. And people don't remember this, but there was a time when-- before search engines when people really struggled to find resources, and there was enormous excitement when search engines came out. And search engines are, in fact, AI. They are based on AI at the back end, coming up with lists of things that hopefully match what you typed in. In fact, the problem with the search engine becomes not trying to find anything, but trying to filter everything to decide what's really useful.
So you can think of ChatGPT as the next step beyond a search engine where instead of getting a list of things and then you decide which might be useful and you examine them, you get an answer that says, this is what I think you want. And that is really more the AI taking charge than it is the AI saying, I can help you. Here's some things that you might look at and decide about. That makes me wary because AI is not at a stage where it really understands what it's saying.
And so it will make up things when it doesn't know them, kind of a not very good student seeing if they can fake out the teacher. And it will provide answers that are not customized to somebody's culture or to somebody's reading level or to somebody's other characteristics. So it's really quite limited.
I know that Harvard has sent some wording out that I've now put into my syllabi about students being welcome to use whatever tools they want. But when they present something as their work, it has to be something that they wrote themselves. It can't be something that somebody else wrote, which is classic plagiarism. It can't be something that Chat AI wrote that they're presenting as their work and so on. I think that what Chat AI does is it raises the bar for human performance.
I know a lot about what people are going through now in terms of job interviews because my older daughter is an HR manager, and my younger daughter just graduated. And she's having a lot of job interviews. And in contrast to earlier times, now, job interviews typically involve a performance.
If you're going to be hired for a marketing position, they'll say bring in a marketing plan when we do our face-to-face interview on this, and we'll evaluate it. Or in her case, in mechanical engineering, they say when you come in, there's this system that you're going to have a chance to debug, and we'll see how well you do it. Those employers are going to type the same thing into Chat AI. And if someone comes in with something that isn't any better than Chat AI, they're not going to get hired because why hire somebody that can't outcompete a free resource?
Jill Anderson: Oh interesting.
Chris Dede: So it raises the bar for human performance in an interesting way.
Jill Anderson: Your research looks at something called intelligence augmentation. I want to know what that means and how that's different from artificial intelligence.
Chris Dede: Intelligence augmentation is really about the opposite of this sort of negative example I was describing where now you've got to outthink Chat AI if you want to get a job. It says, when is the whole more than the sum of the parts? When do a person and AI working together do things that neither one could do as well on their own?
And often, people think, well, yeah, I can see a computer programmer, there might be intelligence augmentation because I know that machines can start to do programming. What they don't realize is that it applies to a wide range of jobs, including mine, as a college professor. So I am the associate director for research in a national AI institute funded by the National Science Foundation on adult learning and online education. And one of the things the Institute is building is AI assistants for college faculty.
So there's question answering assistants to help with student questions, and there's tutoring assistants and library assistants and laboratory assistants. There's even a social assistant that can help students in a large class meet other students who might be good learning partners. So now, as a professor, I'm potentially surrounded by all these assistants who are doing parts of my job, and I can be deskilled by that, which is a bad future. You sort of end up working for the assistant where they say, well, here's a question I can't answer.
So you have to do it. Or you can upskill because the assistant is taking over routine parts of the job. And in turn, you can focus much more deeply on personalization to individual students, on bringing in cultural dimensions and equity dimensions that AI does not understand and cannot possibly help with. The trick about AI is that to get it, we need to change what we're educating people for because if you educate people for what AI does well, you're just preparing them to lose to AI. But if you educate them for what AI can't do, then you've got IA.
Jill Anderson: So that's the goal here. We have to change the way that we're educating young people, even older people at this point. I mean, everybody needs to change the way that they're learning about these things and interacting with them.
Chris Dede: They do. And we're hampered by our system of assessment because the assessments that we use, including Harvard with the GRE and the SAT and so on, those are what AI does well. AI can score really well on psychometric tests. So we're using the wrong measure, if you will. We need to use performance assessments to measure what people can do to get into places like Harvard or higher education in general because that's emphasizing the skills that are going to be really useful for them.
Jill Anderson: You mentioned at the start artificial intelligence isn't really something brand new. This has been around for decades, but we're so slow to adapt and prepare and alter the way that we do things that once it reaches kind of the masses, we're already behind.
Chris Dede: Well, we are. And the other part of it is that we keep putting old wine in new bottles. I mean, this is — if I had to write a headline for the entire history of educational technology, it would be old wine in new bottles. But we don't understand what the new bottle really means.
So let me give you an example of something that I think generative AI could make a big difference, be very powerful, but I'm not seeing it discussed in all the hype about generative AI. And that is evidence-based modeling for local decisions. So let's take climate change.
One of the problems with climate change is that let's say that you're in Des Moines, Iowa, and you read about all this flooding in California. And you say to yourself, well, I'm not next to an ocean. I don't live in California. And I don't see why I should be that worried about this stuff.
Now, no one has done a study, I assume, of flooding in Des Moines, Iowa, in 2050 based on mid-level projections about climate change. But with generative AI, we can estimate that now.
Generative AI can reach out across topographic databases, meteorological databases, and other related databases to come up with here's the parts of Des Moines that are going to go underwater in 2050 and here's how often this is going to happen if these models are correct. That really changes the dialogue about climate change because now you're talking about wait a minute.
You mean that park I take my kids to is going to have a foot of water in it? So I think that kind of evidence-based modeling is not something that people are doing with generative AI right now, but it's perfectly feasible. And that's the new wine that we can put in the new bottle.
Jill Anderson: That's really a great way to use that. I mean, and you could even use that in your classroom. Something that you said a long, long time ago was that — and this is paraphrasing — the idea that we often implement new technology, and we make this mistake of focusing on students first rather than teachers.
Chris Dede: In December, I gave a keynote at a conference called Empowering Learners for the Age of AU that has been held the last few years. And one of the things I talked about was the shift from teaching to learning. Both are important, but teaching is ultimately sort of pouring knowledge into the minds of learners. And learning is much more open ended, and it's essential for the future because every time you need to learn something new, you can't afford to go back and have another master's degree. You need to be able to do self-directed learning.
And where AI can be helpful with this is that AI can be like an intellectual partner, even when you don't have a teacher that can help you learn in different ways. One of the things that I've been working on with a professor at the Harvard Business School is AI systems that can help you learn negotiation.
Now, the AI can't be the person you're negotiating with. AI is not good at playing human beings — not yet and not for quite a long time, I think. But what AI can do is to create a situation where a human being can play three people at once. So here you are. You're learning how to negotiate a raise.
You go into a virtual conference room. There's three virtual people who are three bosses. There's one simulation specialist behind all three, and you negotiate with them. And then at the end, the system gives you some advice on what you did well and not so well.
And if you have a human mentor, that person gives you advice as well. Ronda Bandy, who was a professor in HGSE until she moved to Hunter College, she and I have published five articles on the work we did for the HGSE's Reach Every Reader Project on using this kind of digital puppeteering to help teachers practice equitable discussion leading. So again, here's something that people aren't talking about where AI on the front end can create rich evocative situations, and AI and machine learning on the back end can find really interesting patterns for improvement.
Jill Anderson: You know, Chris, how hard is it to get there for educators?
Chris Dede: I think, in part, that's what these national AI institutes are about. Our institute, which is really adult learning with a workplace focus, is looking at that part of the spectrum. There's another institute whose focus is middle school and high school and developing AI partners for students where the student and the partner are learning together in a different kind of IA. There's a third Institute that's looking at narrative and storytelling as a powerful form of education and how can AI help with narrative and storytelling.
You can imagine sitting down. Mom and dad aren't around. You've got a storybook like Goldilocks and the Three Bears, and you've got something like Alexa that can listen to what you're reading and respond.
And so you begin, and you say, Goldilocks went out of her house one day and went into the woods and got lost. And Alexa says, why do you think Goldilocks went into the woods? Was she a naughty girl? No. Or was she an adventurous girl, or was she deeply concerned about climate change and wanting to study ecosystems?
I mean, I'm being playful about this, but I think the point is that AI doesn't understand any of the questions that it's asking but it can ask the questions, and then the child can start to think deeper than just regurgitating the story. So there's all sorts of possibilities here that we just have to think of as new wine instead of asking how can AI automate our order thinking about teaching and learning.
Jill Anderson: I've been hearing a lot of concern about writing in particular-- writing papers where young people are actually expressing their own ideas, concerns about plagiarism and cheating, which I would say the latter have long existed as challenges in education, aren't really a new one. Does AI really change this? And how might a higher ed or any educator really look at this differently?
Chris Dede: So I think where AI changes this is it helps us understand the kind of writing that we should be teaching versus the kind of writing that we are teaching. So I remember preparing my children for the SAT, and it used to have something called the essay section. And you had to write this very formal essay that was a certain number of paragraphs, and the topic sentences each had to do this and so on.
Nobody in the world writes those kinds of essays in the real world. They're just like an academic exercise. And of course, AI now can do that beautifully.
But any reporter will tell you that they could never use Chat AI to write their stories because stories is what they write. They write narratives. If you just put in a description, you'll be fired from your reportorial job because no one is interested in descriptions. They want a story.
So giving students a description and teaching them to turn it into a story or teaching them to turn it into something else that has a human and creative dimension for it, how would you write this for a seventh-grader that doesn't have much experience with the world? How would you write this for somebody in Russia building on the foundation of what AI gives you and taking it in ways that only people can? That's where writing should be going.
And of course, good writing teachers will tell you, well, that's nothing new. I've been teaching my students how to write descriptive essays. The people who are most qualified to talk about the limits of AI are the ones who teach what the AI is supposedly doing.
Jill Anderson: So do you have any helpful tips for educators regardless of what level they're working at on where to kind of begin embracing this technology?
Chris Dede: What AI can do well is what's called reckoning, which is calculative prediction. And I've given some examples of that with flooding in Des Moines and other kinds of things. And what people do is practical wisdom, if you will, and it involves culture and ethics and what it's like to be embodied and to have the biological things that are part of human nature and so on.
So when I look at what I'm teaching, I have to ask myself, how much of what I'm teaching is reckoning? So I'm preparing people to lose to AI. And how much of what I'm teaching is practical wisdom?
So for example, we spend a lot of time in vocational technical education and standard academic education teaching people to factor. How do you factor these complex polynomials?
There is no workplace anywhere in the world, even in the most primitive possible conditions, where anybody makes a living by factoring. It's an app. It's an app on a phone. Should you know a little bit about factoring so it's not magic? Sure.
Should you become fluent in factoring? Absolutely not. It's on the wrong side of the equation.
So I think just teachers and curriculum developers and assessors and stakeholders in the outcomes of education need to ask themselves, what is being taught now, and which parts of it are shifting over? And how do we include enough about those parts that AI isn't magic? But how do we change the balance of our focus to be more on the practical wisdom side?
Jill Anderson: So final thoughts here — don't be scared but figure out how to use this to your advantage?
Chris Dede: Yeah, don't be scared. AI is not smart. It really isn't. People would be appalled if they knew how little AI understands what it's telling you, especially given how much people seem to be relying on it. But it is capable of taking over parts of what you do that are routine and predictable and, in turn, freeing up the creative and the innovative and the human parts that are really the rewarding part of both work the life.
EdCast: Chris Dede is a senior research fellow at the Harvard Graduate School of Education. He is also a co-principal investigator of the National Artificial Intelligence Institute in adult learning and online education. I'm Jill Anderson. This is the Harvard EdCast produced by the Harvard Graduate School of Education. Thanks for listening.
[MUSIC PLAYING]
| 2023-02-09T00:00:00 |
https://www.gse.harvard.edu/ideas/edcast/23/02/educating-world-artificial-intelligence
|
[
{
"date": "2023/02/09",
"position": 10,
"query": "AI education"
},
{
"date": "2023/02/09",
"position": 6,
"query": "artificial intelligence education"
},
{
"date": "2023/02/09",
"position": 92,
"query": "artificial intelligence graphic design"
}
] |
|
OPINION: ChatGPT poses a threat to journalism
|
OPINION: ChatGPT poses a threat to journalism
|
https://wildcat.arizona.edu
|
[
"Luke Lawson"
] |
However, the use of AI tools also has the potential to detect and prevent academic misconduct by flagging instances of plagiarism and other forms of cheating.
|
“Artificial Intelligence (AI) can potentially pose a threat to academic integrity if it is used to create or generate academic work that is meant to be passed off as original, human-generated content. This is known as ‘contract cheating,’ where students use AI tools to write essays or complete other coursework. However, the use of AI tools also has the potential to detect and prevent academic misconduct by flagging instances of plagiarism and other forms of cheating. Overall, it depends on how AI is being used, but it can both pose a threat and also help to promote academic integrity.”
Interestingly enough, the entire first paragraph was copied and pasted from an AI chatbot called ChatGPT when I asked it, “Is AI a threat to academic integrity?” This chatbot was created by an artificial intelligence company called OpenAI, and it is known for being able to communicate with adequate human language styles and provide information. Its ability to create in-depth sentences opens up an opportunity for students to copy the information it gives them on essays and other assignments, which could be potentially problematic.
Since the answers ChatGPT gives its users are entirely original, this form of plagiarism would not be detected by sites like Turnitin. However, the chatbot does not provide longer overall responses, as most answer lengths are around a paragraph. The information is also fact-based, and students would struggle using its answers to form an argument for certain opinion-based papers. So, this type of artificial intelligence is not going to be ending creative essays or opinion writing anytime soon. Though, this type of factual information may pose a threat to journalists and threaten trustworthy sources.
With its ability to answer user questions and provide factual information, news reporting journalism may be at risk. Similarly, this technology may be used to create convincing fake news stories that sound like they have been generated by real journalists and human writers. This information could then be widespread and cause confusion, creating an untrustworthy news environment. If the bot also produces inaccuracies, it is hard to hold humans accountable for the errors as the information is generated without human input.
Despite these potential problems with the AI, it has seemingly already become favored over Google by many people. ChatGPT can explain complicated topics without requiring users to filter through unrelated and unnecessary sources like on Google. This type of technological progression may be beneficial for those seeking quick information without the annoyance of search engines, but is it worth the potential risks?
I think the answer comes down to what the AI said itself, that it largely depends on how it is being used. Technological progression is both convenient and helpful, so ChatGPT isn’t necessarily a bad thing. However, if it is being used to promote false information and simultaneously brings an end to news journalism, the way we receive information may completely change in the future. I do not think that plagiarism in academic settings should be the first concern when it comes to artificial intelligence, but its ability to infiltrate human work and human lives so easily.
Follow the Daily Wildcat on Twitter
Luke Lawson (he/him) is a sophomore intending to major in accounting. He enjoys discussing political events, hiking and watching films.
| 2023-02-09T00:00:00 |
https://wildcat.arizona.edu/140712/opinions/opinion-chatgpt-poses-a-threat-to-journalism/
|
[
{
"date": "2023/02/09",
"position": 27,
"query": "AI journalism"
}
] |
|
It's time to challenge the narrative about ChatGPT and ...
|
It’s time to challenge the narrative about ChatGPT and the future of journalism
|
https://www.poynter.org
|
[
"Jenna Burrell",
"Jenna Burrell Is Data",
"Society S Director Of Research. She Oversees All Aspects Of Our Research Program At Data",
"Society",
"Ensuring The Rigor",
".Wp-Block-Co-Authors-Plus-Coauthors.Is-Layout-Flow",
"Class",
"Wp-Block-Co-Authors-Plus",
"Display Inline",
".Wp-Block-Co-Authors-Plus-Avatar"
] |
But in the face of AI hype, journalism is also culpable, with headlines like ... That, of course, has always been the journalist's job — and despite AI's ...
|
We need to challenge the notions about automation that seem to be carried along in conversations about ChatGPT and other forms of “artificial intelligence” — notions including that AI acts on its own and that it threatens to replace humans.
The results of a Google image search for “artificial intelligence” or “machine learning” are telling: lots of pictures of brains, robots and humanoid-type figures. Anthropomorphizing automated technologies reveals our fascination with them, but it gets in the way of a meaningful understanding of how they work, and how they impact us.
As an academic, formerly as a professor at UC Berkeley and now director of research at the nonprofit research institute Data & Society, I’ve devoted my career to studying the relationship between digital technology and society. I’m committed to using my research to nudge policymakers and experts of all stripes toward a more humane and human-centered approach to computing technology.
In fact, human labor plays an important role in AI tools. It’s human labor that trains these models, based on data produced by humans: We teach them what we know. And around the world, it’s on-call human workers who fix errors in the technology, respond when tools get stuck, moderate content, and even guide robots along city streets.
Take ChatGPT, which has captivated so many imaginations since its public launch in November. This chatbot responds to prompts with extraordinary fluidity — it gives immediate plausible-sounding answers to questions, provides expert-sounding explanations, and can write longish texts with stylistic flourishes. But while its abilities might seem uncanny, the explanation is comparatively simple: What made ChatGPT possible is the global move of everyone and everything online — the mass digitization of everyday life, resulting in the extraordinarily broad text corpus that is the internet. ChatGPT sucks up all of that text and uses it to predict patterns, to devise sequences of words.
Here is just some of what ChatGPT does not do: research, fact-checking, or copyediting at a minimally adequate level. Indeed, ChatGPT is proof that finding “truth” is a lot trickier than having enough data and the right algorithm. Despite its abilities, ChatGPT is unlikely to ever come close to human capabilities: its technical design, and the design of similar tools, is missing fundamental things like common sense and symbolic reasoning. Scholars who are authorities in this area describe it as being like a parrot; they say its responses to prompts resemble “pastiche” or “glorified cut and paste.”
When you think of ChatGPT, don’t think of Shakespeare, think of autocomplete. Viewed in this light, ChatGPT doesn’t know anything at all.
Some of the misunderstandings can be traced back to the language computer scientists have long used to describe this type of research. “Machine learning” and “intelligence,” for example, could more accurately be “data mining” or “statistical optimization.” These terms sound more like technical jargon, but they don’t carry the misleading connotations of references to “intelligence.”
But in the face of AI hype, journalism is also culpable, with headlines like this one from The New York Times: “Meet GPT-3. It Has Learned to Code (and Blog and Argue).” Articles meant to serve as correctives still fall into anthropomorphism, like a piece in Salon that said “AI chatbots can write, but can’t think.” Even the claim that ChatGPT can “write” is an exaggeration, an interpretation of the tool’s capabilities that inflate the reality of it and contribute to further misunderstandings and overstatements that have real consequences.
Depending on whether we find viable and valuable uses for it, it’s true that ChatGPT could be part of a broader shift and redelegation of how journalism is done. What we need to avoid is using it to replace humans, which it does ineptly — flooding the internet with even more unreliable (but plausible-sounding) junk. CNET recently made the mistake of overestimating AI’s ability, yielding not only a series of articles rife with factual errors but a broader reckoning for the company and perhaps the industry at large.
One thing we learn in scholarship on the history of technology is that there are very often outrageous expectations set for tech at its invention. Airplanes will bring about world peace. Movies will make schools obsolete. We have the advantage of being able to look to that history and see that in fact, no technology is inevitable and that the march of progress (while relentless) takes many, many unexpected turns along the way.
Journalists are well-positioned to help fight the hype. Don’t let these tools dazzle you beyond reason. Don’t anthropomorphize them. Ask hard questions about what they’re purported to do.
That, of course, has always been the journalist’s job — and despite AI’s influence, it’s one that’s not going anywhere.
More from Poynter:
| 2023-02-09T00:00:00 |
2023/02/09
|
https://www.poynter.org/commentary/2023/opinion-chatgpt-will-not-replace-humans/
|
[
{
"date": "2023/02/09",
"position": 42,
"query": "AI journalism"
}
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.