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Transforming Your Business with AI - INSEAD
Transforming Your Business with AI
https://www.insead.edu
[ "Theodoros Evgeniou", "Phanish Puranam", "The Roland Berger Chaired Professor Of Strategy", "Organisation Design", "Research Director Of The Insead-Wharton Alliance", "Ville Satopaa" ]
Discover the power of AI transformation. Learn AI course for business leaders and how to formulate effective AI strategy for your organisation's needs.
UPDATED CONTENT: Innovation in artificial intelligence—in deep learning, generative AI, as well as other emerging approaches—is unlocking unprecedented opportunities and redefining what organisations can achieve across every sector. Yet, realising the full potential of AI demands a clear understanding of its risks and complexities. As organisations recalibrate their business models for the AI era, success depends on their ability to effectively conceive, design, adopt, and integrate these powerful tools. This requires a unique blend of business acumen, management expertise, and technical know-how—coupled with a strategic understanding of risk, regulation, and policy at both national and international levels. Transforming Your Business with AI is designed to equip managers and leaders with the essential knowledge and skills to drive and sustain AI-powered business transformation. The programme offers a robust foundation in key technical principles, while highlighting how technology, organisational strategy, and culture must align for successful integration and lasting impact. You will gain the vocabulary, insight, and confidence to bridge data science, business, and strategic stakeholders—and become a catalyst for AI-driven innovation within your organisation
2022-07-14T00:00:00
2022/07/14
https://www.insead.edu/executive-education/open-online-programmes/transform-business-ai
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AI Business Essentials for Leaders Course - QA
AI Business Essentials for Leaders Course
https://www.qa.com
[]
You will learn how you could assess your organisation for an AI-ready culture, consider who key stakeholders would be and how AI projects can be implemented ...
This course offers you a one-day comprehensive introduction to the world of Artificial Intelligence (AI) tailored for business professionals who are looking to make effective changes involving AI solutions. Artificial Intelligence (AI) will define the next generation of software solutions and unlock the potential to create amazing applications that improve life for everyone provided we plan changes carefully and with safety in mind. We begin by demystifying the basics of Machine Learning and AI and through practical activities you will become comfortable with surrounding terminology, common use cases, and risks. You will learn how you could assess your organisation for an AI-ready culture, consider who key stakeholders would be and how AI projects can be implemented while fostering a culture that encourages responsible and trustworthy use of AI. Please note - If you would prefer a shorter course, private deliveries are available in which you may choose any two of the course modules for you and your group to experience. Please contact us to request your combination. Target Audience The Artificial Intelligence Business Essentials course is focussed on individuals with an interest in, (or need to implement) AI in an organisation, especially those working in the following capacities:
2022-12-01T00:00:00
https://www.qa.com/course-catalogue/courses/ai-business-essentials-for-leaders-qaaibe/
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AI for Business Leaders - The University of the West Indies, Mona
Mona School of Business & Management
https://www.mona.uwi.edu
[]
This course covers AI's practical applications, ethical considerations, and strategic advantages, empowering leaders to make informed, forward-thinking ...
At the end of the AI for Business Leaders course, participants will understand how to leverage the power of artificial intelligence to drive business transformation. This course covers AI’s practical applications, ethical considerations, and strategic advantages, empowering leaders to make informed, forward-thinking decisions in a rapidly evolving digital landscape.
2022-12-01T00:00:00
https://www.mona.uwi.edu/msbm/professional-services-unit/courses/ai-business-leaders
[ { "date": "2022/12/01", "position": 95, "query": "AI business leaders" }, { "date": "2023/01/01", "position": 94, "query": "AI business leaders" }, { "date": "2023/04/01", "position": 96, "query": "AI business leaders" }, { "date": "2024/11/01", "position": 95, "query": "AI business leaders" } ]
Applying XAI to an AI-based system for candidate ...
Applying XAI to an AI-based system for candidate management to mitigate bias and discrimination in hiring
https://link.springer.com
[ "Hofeditz", "Lennart.Hofeditz Uni-Due.De", "Universität Duisburg-Essen", "Duisburg", "Clausen", "Suenje.Clausen Uni-Due.De", "Rieß", "Alexander.Riess Uni-Due.De", "Mirbabaie", "Milad.Mirbabaie Uni-Paderborn.De" ]
by L Hofeditz · 2022 · Cited by 78 — This work investigates the impact of an AI-based system's candidate recommendations on humans' hiring decisions and how this relation could be moderated by an ...
Why AI recommendations might not reduce race-based discrimination in hiring The participants’ selection of foreign-race candidates was not in line with existing literature on racial discrimination in hiring, which has found that race continues to be one of the main sources of discrimination in hiring today and that Turkish individuals are especially discriminated against in Germany (Baert, 2018; Quillian et al., 2017, 2019; Zschirnt & Ruedin, 2016). This was generally not the case in our study, as the control group without recommendations and explainability showed a high number of selections of foreign-race candidates. However, if the AI-based system recommended a foreign-race candidate, the candidate was less likely to be selected. Thus, the AI-based system’s recommendations did not increase the selection of foreign-race candidates, and Hypothesis 1 was not supported. Instead, participants who received the recommendations tended to select fewer foreign-race candidates than participants who did not receive recommendations. As the BFI-scores of the participants in the experimental groups receiving AI recommendations did not differ significantly from the groups without AI recommendations (see Table 8 in Appendix 5), this difference does not appear to result from personality differences of the participants in the respective groups. We suggest that the implemented AI recommendation did not work as assumed because of algorithmic aversion (Berger et al., 2021; Dietvorst et al., 2015; Ochmann et al., 2021). Although algorithmic aversion usually occurs if people with domain knowledge can select between a human and an algorithm recommendation (Dietvorst et al., 2015), some previous research has suggested that there are cases of algorithm aversion occurring even if there is no human recommender alternative (Bigman et al., 2021). The qualitative analysis also provides evidence for this, suggesting that participants with domain knowledge in HR relied less on the AI recommendations compared to participants without domain knowledge. Accordingly, there is a possibility that the participants were indeed averse to AI, which led to a rejection of the recommended candidate and an increased selection of German candidates. This could be another indicator that algorithmic aversion can occur even without offering a human alternative, as suggested by Bigman et al. (2021). To avoid possible aversion, AI-based systems might be used to some extent as part of new task designs that balance human and system characteristics through mutual delegation (Baird & Maruping, 2021). Another approach to mitigating aversion is to get affected individuals better involved in the AI adaptation process as part of organizational learning (Wijnhoven, 2021). On the other hand, the lower reliance on the AI recommendations of some of the participants might also be due to a higher degree of self-confidence in selecting the right candidate, as recent research has found that self-confidence influences the adoption or rejection of AI augmentation (Chong et al., 2022). As the reasons provided by participants with and without HR practice differed only slightly and participants could not select between a human and an algorithmic advisor, further explanations than aversion and self-confidence need to be taken into account. Considering the qualitative results, the low number of reasons given based on a candidate’s race suggests that participants did not pay much attention to the race of candidates or that they were trying to be as objective as possible in decision-making. This could indicate that the selection decisions were, in fact, predominantly made based on qualifications. While the overall qualification (sum of stars) was identical for the candidates, the individual scores for qualifications differed slightly. However, it is also possible that participants were not aware of or avoided mentioning the role of the candidate’s race in their selection, either because they were not aware of their own biases or because they did not want to admit them (i.e., the answers might be subject to a social desirability bias). Examining the participants’ reasons in more detail, we found that programming experience was the most frequently mentioned reason for the decision in the first job round in which race was the sensitive attribute. We therefore assume that the reason for not finding an effect of AI recommendation on selecting foreign-race candidates could be that the majority of our participants were sure that programming skills comprised the most important criterion for the role of IT administrator even though other skills were mentioned in the job description. Thus, an AI recommendation does not seem to be effective when there is already a clear qualification-based indicator for a decision. This could be explained by a high level of confidence that results in the avoidance of following AI recommendations. The result of the personality test (BFI-10) could also be used to explain the lack of evidence for discrimination in the initial candidate selection. A high level of openness (see Table 8 in Appendix 5) indicates that the participants think unconventionally and are open to new things (John & Srivastava, 1999). This could foster consideration of the overall qualification of the candidates regardless of their demographics and thus, result in less discrimination. However, we did not find systematic differences in personality between the relevant groups. When considering the results for Hypotheses 2 and 3, it becomes apparent that the AI-based system’s recommendations can also work as expected in cases where participants perceive less clear qualification-based criteria for job profiles than was the case with programming for the first job. AI recommendations can reduce age- and gender-based discrimination When examining candidate selection in the control group, it becomes apparent that compared to the attributes of race and age, the participants selected female candidates considerably less often. This reinforces the evidence in the literature regarding discrimination against female candidates in hiring (Baert, 2018; Carlsson & Sinclair, 2018; Kübler et al., 2018). The qualitative data rather signaled that if participants mentioned gender as a reason for selection, they emphasized positive (yet partially stereotypical) aspects of hiring women (e.g., being good for team morale). This suggests that the negative discrimination against women shown by the quantitative results happened unconsciously or that participants deliberately concealed the discrimination. The quantitative finding that AI recommendations can increase the selection of older and female candidates (H2 and H3) can be further strengthened by the qualitative results, which reveal that 13% and 17%, respectively, of the participants who received recommendations mentioned it as a reason for their candidate selection. In addition, participants stated that they used the recommendations to make decisions in cases of uncertainty. Regarding the second hypothesis, where we considered whether an AI-based system’s recommendations impact the selection of older candidates, it was supported and showed a medium-sized effect. This implies that the recommendations led to more frequent selection of older candidates. These findings are strengthened by the qualitative findings, in which the participants mentioned the recommendation as a reason for their selection. Furthermore, the participants’ ethical position (EPQ) indicated that they possessed rational and diverse candidate selection behavior. The findings for the sensitive attribute age (H2) are also in line with current literature regarding discrimination, which shows that older candidates are subject to discrimination in hiring (Baert, 2018; Lössbroek et al., 2021; Neumark et al., 2017; Zaniboni et al., 2019). In summary, the AI-based system’s recommendations positively influenced the participants’ selection decisions for older and female candidates. Comparing the participants with and without HR experience, those with HR experience mentioned age more often as a reason for their decision. If we assume that a candidate was selected mainly because of their age and not because of a certain skillset, we consider this a case of age discrimination (Baert, 2018; Neumark, 2021; Richardson et al., 2013; Zaniboni et al., 2019). However, AI-based recommendations showed a positive effect on the selection of an older candidate for both groups. The role of XAI in AI-based systems for hiring Our findings suggest that XAI-induced transparency, that is, providing participants information about the functionality of the AI-based system, did not moderate the effect of the system’s recommendations on the selection of older and female candidates (H4.2 and H4.3 rejected). It appears that emulating the processing of an AI-based system by providing a high-level explanation of the input–output relation of the data did not – as would be expected based on the suggestions of Gilpin et al. (2018) – increase the participants’ trust in and acceptance of the system’s recommendations. Thus, these findings seem to challenge expectations highlighting the effectiveness of and general need for XAI (Adadi & Berrada, 2018; Dwivedi et al., 2021; Gunning et al., 2019). One reason for this might be that there is a wide range of XAI types (see, e.g., Giudotti et al. (2018) for an overview) and that a different XAI type would have been more suitable to support the target audience. However, as XAI-induced transparency positively moderated the selection of foreign-race candidates (H4.1 supported), the effectiveness of XAI might also depend on the content of the decision task. Previous research has already emphasized that a successful application of XAI depends on various quality criteria, such as fidelity, generalizability, explanatory power, interpretability, comprehensibility, plausibility, effort, privacy, and fairness, depending on the target group (Meske et al., 2022). Here, with H4.2 and H4.3 not being supported and H4.1 being supported, our findings suggest that not only quality criteria and XAI type but also the content of the decision task need to be considered. With these findings, we addressed the research gap identified by Adadi and Berrada (2018), who argued that the role of humans in XAI is inconclusive and can only be attributed to undiscovered influencing factors. We provided empirical evidence for the context of discrimination in hiring and tested XAI in the context of participants’ ethical position and personality traits. In addition, our findings suggest that the content for achieving XAI-induced transparency should be individually adaptable to user qualifications. This is in line with Shin (2021), who argued that algorithmic experience in AI needs to be addressed in practice and that heuristics and cognitive processes need to be incorporated into the design of these algorithms, making them user-centric. Furthermore, based on our findings, more research is needed regarding the mechanisms of XAI on humans and their influencing factors, which was also one of the research opportunities outlined by Meske et al. (2022) for XAI in information systems. In addition, we provided empirical evidence on how a higher degree of transparency leads to better understanding of potentially undesired practices in the offline world (e.g., gender bias and discrimination), which was mentioned as a promising research direction by Meske et al. (2022). We addressed both knowledge on XAI in the context of individual attributes and knowledge on how XAI and transparency can lead to less discrimination and bias in hiring. Limitations and further research The study adopted a fairly broad, high-level type of XAI in which participants received a general explanation about the processing of data in the system as well as its goal of augmenting decision-making in hiring to reduce discrimination. However, there are many other, more technically detailed XAI approaches that could prove (more) effective in this context (see, e.g., Adadi & Berrada, 2018 or Gilpin et al., 2018). While this study focused on a target audience (and a corresponding sample) of non-AI experts, we acknowledge that this might be an insufficiently detailed characterization of HR professionals. In addition, a relatively large number of participants were educated, female, and from Germany, and only about one-third of the participants reported prior HR experience. Therefore, the findings are subject to limited generalizability to HR professionals. The candidate management platform was designed to resemble prevalent AI-based systems for this purpose; however, the findings might not be generalizable to other platforms in this domain. The overall qualification of the candidates (sum of stars) was identical for both candidates in each round; the star ratings for specific qualifications differed between the two candidates. While this was necessary to gain insights on participants’ tendency to consider demographic information for deciding between candidates, it introduced the risk that the participants’ perceived relevance of certain qualifications for a job influenced their selection. Also, the effects might differ if participants had to select candidates from a larger pool of candidates on the platform rather than making a choice based on a direct comparison of two candidates. Lastly, the cultural context in which the platform is deployed might make a difference as for example the influence of AI recommendations could be more pronounced in highly technology-affine societies. Addressing these limitations, future research could explore the (dis-)advantages of different types of XAI from the perspective of HR professionals in greater depth. It would be interesting to conduct the study in a real HR environment and limit participation to experienced HR employees. As the sensitive attributes leading to discrimination might differ depending on contextual factors (e.g., culture) or individual factors (e.g., characteristics of the decision maker), future studies should aim to explore the effects of AI recommendations and XAI with different sensitive attributes (e.g., disability) and a diverse group of HR professionals. Furthermore, to dive deeper into possible causes for the observed candidate selection behavior and the effectiveness of AI recommendations and XAI, future research could measure algorithmic aversion, automation bias, cognitive load, or the effect of mistrust disposition. Future research should consider directly measuring these aspects in the context of XAI and AI recommendations for candidate selection and examine possibilities to mitigate aversion, for example, by incorporating AI-based information systems as part of new task designs that balance human and systemic characteristics through mutual delegation and through organizational learning processes with strong stakeholder participation in AI adoption. Additionally, to improve generalizability, future research could investigate XAI and AI recommendations on different types of candidate management platforms and in alternative deployment contexts (e.g., other countries). Lastly, we focused on the point of view of the recruiter and not on those who are affected by discrimination or bias in hiring. Future research needs to go a step further and, for example, follow a discourse ethics approach based on that of Mingers and Walsham (2010) by also involving other stakeholders in the debate about diversity in XAI-based recommendations. Contribution to research The findings of this study contribute to research on augmenting human decision-making with AI-based systems in several ways. First, we showed that in decision-making scenarios with no clearly preferable option, providing AI recommendations and XAI can influence decision-making and potentially reduce discrimination in hiring. Second, our findings suggest that a clear association between a qualification-based criterion and a decision outcome limits the impact of AI recommendations on decision-making. Third, our exploratory analysis indicated that participants with domain knowledge did not behave differently in response to AI recommendations and/or XAI than participants without domain knowledge. Fourth, we open a new field of research regarding the combination of XAI and AI-based system recommendations to augment decision-making in the context of hiring. We also contribute to the literature on XAI by empirically testing the influence of XAI on the effectiveness of augmenting decision making with an AI-based system in the context of hiring. As the effects of XAI differed for the sensitive attributes, our findings suggest that, in addition to quality criteria and target groups (Meske et al., 2022), the content or context of the decision plays a role in the impact of XAI. Furthermore, this research extends the literature concerning the reduction of discrimination in hiring (e.g., Foley & Williamson, 2018; Krause et al., 2012) and presents recommendations regarding an AI-based system as a promising approach for reducing discrimination against older and female candidates in hiring. Moreover, the findings argue for the positive benefits of using AI to reduce discrimination and bias, complementing the literature that discusses the ethical issues of AI in hiring (Lepri et al., 2018; Raghavan et al., 2020). Finally, the study contributes to broadening the understanding of AI in society by demonstrating a new beneficial use case of applying XAI to reduce discrimination in hiring. Contribution to practice This research also provides practical implications for stakeholder groups working with XAI, such as AI managers, AI developers, AI users, and individuals affected by AI-based system decisions and recommendations. On the one hand, the study contributes to increasing general welfare by examining an important topic for society and electronic markets. Thus, our findings might lead to greater diversity in future workforces and positively affect individuals with sensitive attributes who are subject to AI-based system recommendations. For example, recruiters as AI users can augment their decision making with similar systems, reflect on their (potential) biases, and better understand the reasons for AI-based system recommendations through XAI. On the other hand, this research can draw the attention of organizations and AI managers to the issue of discrimination remaining an important problem in hiring. Furthermore, the platform conceptualized and developed in this research can be a starting point for developing a system for training HR staff on discrimination in hiring. XAI and recommendations from AI-based systems can be effective, but they may require further action from the organization to achieve diverse hiring in the long term. For practical application purposes, XAI might be successful in areas where users are in more frequent contact with the technology. Complementing XAI, the implementation of AI recommendations might be a suitable method to realize the AI’s purpose of, in this case, countering discrimination in hiring. Moreover, in general, educating different stakeholders of XAI about AI’s potential dangers and benefits would be advisable to reduce prejudice and fear and increase general acceptance of AI. From an organizational perspective, a question arises as to the overall benefits of XAI for their business. Not every organization that uses an AI-based system necessarily needs to understand the reasons for its outcomes. In addition, some algorithms must be developed from scratch to allow for the ability to explain the processes and reasons for decisions afterward. This leads to an immense amount of work, which may not justify the perceived benefits of XAI in every context. Therefore, incentives are needed that could counteract some of the barriers to the implementation of XAI to ensure more diversity and fewer biases through XAI and AI based-system decisions and recommendations.
2022-12-14T00:00:00
2022/12/14
https://link.springer.com/article/10.1007/s12525-022-00600-9
[ { "date": "2022/12/01", "position": 2, "query": "AI hiring" } ]
4 ways to avoid bias with AI recruitment tools
4 ways to avoid bias with AI recruitment tools
https://www.blg.com
[]
4 best practices when your recruiter uses AI tools · 1. Ask questions about the AI recruitment software · 2. Look carefully at your contract · 3. Comply with ...
4 ways to avoid bias when your HR agency uses AI recruitment tools @Model.HeaderTag> Opinion is split on the use of artificial intelligence in human resources, and organizations should know the pros and cons of using these systems, particularly if they outsource to service providers that use AI recruitment tools. This article summarizes the controversy, touches on proposed Canadian legislation, and offers four best practices to avoid introducing bias into hiring processes — including steps to stay compliant with privacy laws and employment standards. Artificial intelligence in recruitment: Friend or foe? AI-driven technology is used in talent recruitment for everything from ad targeting and resume scoring to analyzing publicly available online information about candidates and evaluating their communication and technical skills during interviews. Champions of the technology look at machine learning tools as a boon to the under-resourced HR department looking for time- and cost-efficient ways to fill vacant positions and manage a landslide of applicants. Some even say AI can reduce bias and meet internal and legislated equity goals in the hiring process — after all, how could machines be prejudiced? Detractors, in contrast, argue the opposite, pointing to past examples of AI recruiting software that were discontinued after discovering that their algorithms were discriminating against women. Problems arise, critics say, because machines are trained to identify the best candidates using existing data, which introduces systemic biases. A resume scoring system, for example, may look for (or exclude) a particular gender, pattern of employment, education and even postal code, based on what the existing talent in that role is like. This reproduces the hiring biases of the past and eliminates potentially excellent candidates because they break the mold. This can result in human rights or pay equity liability for companies — even if biases were wholly unintended. According to a recent study from Cambridge University, technology that uses image and video analysis to assess a candidate’s organizational fit, emotional intelligence and problem-solving ability during an interview is even more concerning. One of the lead researchers has said this technology has no scientific basis and is little more than “modern phrenology.” Given that human rights legislation would not allow a company to merely blame discriminatory hiring practices on “the algorithm,” companies ought to be cautious in entrusting their hiring to software without significant human oversight. What laws apply to AI recruitment tools? There is currently no provincial or federal regulation of private sector development and use of artificial intelligence in Canada — although there are laws regarding how employers in Canada can collect, use and disclose identifiable employee data (such as gender, race and level of education). That’s set to change if the Artificial Intelligence and Data Act proposed in federal Bill C-27 passes into law. The draft legislation, which was introduced in June 2022 and will have significant business impacts, is meant to protect individuals from harm — including economic loss — and prevent biased output when machine learning software is used. The Canadian AI proposal takes its cue from the Treasury Board of Canada Secretariat directive on automated decision-making and proposed EU legislation. Canada’s proposal focuses on high-impact systems. While the definition of high impact will be established by regulation, AI systems that can have significant consequences on a person’s wellbeing, employment and economic stability are expected to be considered high impact. Recruitment for a job certainly falls into this category, given the difference it could make in someone’s life if they are eliminated from a job competition or discriminated against by biased algorithms. In Québec, privacy laws are changing following the passage of Bill 64. As of September 2023, organizations will have to disclose if they use a system where decision-making is based on entirely automated processing of personal information. They must also be able to provide information about the personal information that was used to render an automated decision and the factors, parameters and reasons that led to that decision. Organizations may also have to perform a privacy impact assessment before using automated-decision systems as a result of these regulatory changes. 4 best practices when your recruiter uses AI tools If your organization relies on third party recruiters to help identify and screen candidates, you may have little visibility into the AI tools being used — but you need to ensure you’ve done your due diligence to both avoid bias and comply with legislation. These four best practices will help you do so. 1. Ask questions about the AI recruitment software To be a meaningful conversation, the right parties need to be talking. Ask the recruitment agency if you can meet with the data scientist that looks after the software product the recruiter uses, the developer supervising work on the project and the business contact at the software company. Bring along someone from your IT or software development group who is comfortable talking about — and translating — the technological aspects of AI. You’ll also need someone familiar with systemic bias (think chief talent officer or the head of equity, diversity and inclusion). Having your own data scientist at the table can be very helpful. If your organization doesn’t have one, François Joli-Coeur can help you identify consultants familiar with AI software and bias. Focus your conversation on the three topics below. Software development. Is the software development team diverse? Does the software focus on skills over demographics? Does it remove gender, names, photographs and addresses — information that can introduce bias — from the database? Is the dataset the system uses to learn large and diverse? Does the service provider’s contract with the AI software vendor include a representation about the software’s fairness? The answers to all of these questions should be “yes.” Human oversight. While some software claims to use algorithms to increase the diversity of job candidates, human involvement may still be necessary to identify bias. Does the recruiting agency do any audits of their tools to look for bias? And are the humans acting as oversight trained to look for bias, discrimination and non-equitable practices that may violate the applicable human rights legislation or incur liability? If biases are detected, is the software taught to adapt to counterbalance them? External review. Has the system been reviewed by a third party to determine whether it was built in a responsible way? While there isn’t an international standard or certification for AI currently, organizations can be hired to perform an ethics and human rights assessment. Organizations must be sure to consider employment, immigration, pay equity and human rights liabilities in this respect, particularly as they pertain to extending offers of employment to candidates (or excluding candidates from consideration). 2. Look carefully at your contract Typically, the HR service provider will send only the candidates that the AI software identifies as suitable. It is possible to negotiate your contract to allow your HR team, including your equity, diversity and inclusion committee, to review the candidates that were rejected so you can do your own due diligence to surface any biases. Machines learn through data, and a large dataset is one way developers can combat bias. As a result, service providers often include the right to anonymize the information that is collected from applicants so it can be used by the software company to refine the AI recruitment tool’s algorithms. This has privacy implications (see #3 below), and it may be something you wish to remove from your contract. 3. Comply with privacy legislation There may not be any laws governing the development and use of AI in Canada yet, but privacy commissioners can apply aspects of privacy legislation to AI. Under privacy laws, private sector organizations must generally: Only use personal information for the purpose it was collected unless consent was received. Have security safeguards in place. Be open and transparent about how personal information is being used in algorithms. Be able to explain how they avoid bias and discriminatory outcomes in their application of AI to personal information. We recommend you tell potential candidates that artificial intelligence is being used in your hiring processes and that their data may be anonymized and used by the AI product manufacturer for machine learning. You should also be able to answer any questions a candidate has about the use of AI recruitment tools by the service provider. 4. Develop an algorithmic impact assessment scorecard Large organizations that hire for higher-level, career-oriented positions may want to consider developing an algorithmic impact assessment tool if their HR service providers use AI. In the simplest terms, an algorithmic impact assessment helps organizations better understand and manage the risks associated with artificial intelligence. The federal government has developed a scorecard and made it available for use by all. If you decide to proceed with your own algorithmic impact assessment, we can explain what you need to do, assist with assessment criteria, help determine potential impact, identify mitigations and connect you to technical experts so the analysis is integrated. Next steps In the end, AI hiring tools are nothing more than machines crunching numbers. It’s up to the humans that develop the software, as well as those that use it, to be aware of the potential for bias and take the steps necessary to avoid it. If you’d like to have a conversation about the use of AI in your hiring processes, particularly in preparation for upcoming regulations, reach out to any of the key contacts below. We can help you prepare for a conversation with your recruitment agency, suggest wording for the contract, ensure you’re complying with privacy legislation, and advise you on the pros and cons of developing your own algorithmic impact assessment based on the Treasury Board Secretariat’s model. Then we can guide you through the next steps once your hiring decisions have been made, including offers of employment, collection of employee data and managing the employment relationship. In the end, you’ll feel confident that the AI recruitment tools used by your service provider aren’t introducing bias into your hiring processes and will be well prepared for existing and new legislation.
2022-12-04T00:00:00
2022/12/04
https://www.blg.com/en/insights/2022/12/4-ways-to-avoid-bias-when-your-hr-agency-uses-ai-recruitment-tools
[ { "date": "2022/12/01", "position": 5, "query": "AI hiring" } ]
2022–2025 video game industry layoffs
2022–2025 video game industry layoffs
https://en.wikipedia.org
[]
The video game industry experienced mass layoffs in a wave which began in 2022 and peaked in January 2024. An estimated 35,000 jobs were lost from 2022 to ...
The video game industry experienced mass layoffs in a wave which began in 2022[1] and peaked in January 2024. An estimated 35,000 jobs were lost from 2022 to May 2025.[2][3][4][5][6][7] These layoffs had reverberating effects on both established and emerging games companies, impacting employees, projects, and the overall landscape of the games industry.[8] Major job cuts took place at Embracer Group, Unity Technologies, Microsoft Gaming, Electronic Arts, Sony Interactive Entertainment, Epic Games, Take-Two Interactive, Ubisoft, Sega, and Riot Games. The layoffs caused several video games to be canceled, video game studios to be shut down or divested from their parent company, and thousands of employees to lose their jobs.[9] Games industry layoffs by quarter [ 10 ] [ 11 ] Quarter Number of layoffs Q1 2021 287 Q2 2021 90 Q3 2021 45 Q4 2021 145 Q1 2022 1,800 Q2 2022 3,222 Q3 2022 1,149 Q4 2022 2,378 Q1 2023 2,417 Q2 2023 2,757 Q3 2023 2,036 Q4 2023 3,256 Q1 2024 8,619 Q2 2024 2,340 Q3 2024 1,742 Q4 2024 1,938 Q1 2025 1,620 Q2 2025 1,852 The COVID-19 pandemic led to an increase in interest in gaming globally, and was a period of dramatic expansion in the industry, with many mergers and acquisitions conducted. In many cases companies over-expanded, as this rapid COVID-era growth was unsustainable. The industry began to slow in 2022, and amid spiralling costs and a shift in consumer habits, layoffs began. These were primarily limited to China and Russia to begin with, with the Chinese industry adversely affected by a licensing freeze and the Russian industry by the Russian invasion of Ukraine respectively.[12][13] From 2023, most of the job cuts occurred in North America and Europe, with the video game industry in the United States being the most affected, followed by Canada, the United Kingdom and Poland.[14][3] Over 30 video game development studios laid off their entire staff and shut down.[15][16][17][3][18][5] Some of the most notable company closures include: Monolith Productions, Arkane Austin, The Initiative, Ready at Dawn, Volition, London Studio, Pixelopus, Riot Forge, Hypixel Studios and others. A new survey by the International Game Developers Association (IGDA), based on 2023 data, suggests a global unemployment rate of 4.8% within the game industry. Some industry experts believe that the rate in the United States could have doubled by May 2024.[19] Executive Director of Circana (The NPD Group), Mat Piscatella suggests that the most optimistic projection indicates a potential decrease of about 2% for American video game industry in 2024. However, a more pessimistic perspective could see a decline of around 10%, with the possibility of an even greater downturn if conditions worsen significantly.[20] According to a report by DDM Games, the industry is currently in a "reset phase." Companies are restructuring their operations through closures, layoffs, and divestitures. The pandemic-induced growth surge has subsided, leading to a need for recalibration.[21] AI is a concern for many developers also, though there is no indication that layoffs have been driven directly by its adoption. It may however have impacted illustrators and other professions particularly exposed to automation.[22] Causes [ edit ] The layoffs were not a singular event but rather the culmination of several converging factors. The COVID-19 pandemic unexpectedly fueled a surge in video game demand.[23] This led companies to make ambitious investments in acquisitions, mergers, and staff expansion, anticipating sustained growth.[24] However, as the world reopened and the market returned to pre-pandemic trends, the rapid growth proved unsustainable, and companies found themselves with bloated operational costs, necessitating cutbacks.[25] Rising development costs [ edit ] The cost of developing AAA games has steadily climbed in recent years due to several factors. The increasing complexity of game design, the adoption of advanced technologies to create "visually stunning" experiences, and rising player expectations for expansive and cinematic content all contributed to this cost inflation.[26][27] This put immense pressure on company budgets.[28] The global economic slowdown in 2024, coupled with rising interest rates, made it more challenging for companies to secure funding. This limited their ability to invest in new projects and maintain existing ones, further contributing to the need for workforce reductions.[26] According to a report cited by the Competition and Markets Authority (CMA), development budgets for AAA video games have surged in recent years.[29] While AAA releases previously had budgets ranging from $50–150 million, games set for release in 2024 or 2025 are now seeing budgets of $200 million and higher. Some franchises, like Call of Duty and Grand Theft Auto, have budgets exceeding $250 million and $300 million, respectively. Additionally, according to the CMA, one major publisher mentioned that a single AAA game could have development costs between $90–180 million and marketing budgets ranging from $50–150 million.[26] For certain franchises, such as one cited by the CMA, combined development and marketing costs reached $660 million and almost $550 million, respectively.[30] Activision noted the increasing need for multiple studios to meet the demands of annual Call of Duty releases, leading to greater reliance on outsourcing.[31] According to Bloomberg, video game executives anticipate a trend towards big-budget games that take fewer risks and rely on well-established intellectual properties (IP), especially as game development costs continue to rise. Martin Sibille, Vice President at Tencent Games and a former EA executive, highlighted the increasing difficulty in taking risks within the industry.[32] Rising development costs have prompted video game publishers to either cancel or delay their games and lay off development teams. The Embracer Group notably announced the cancellation of 29 titles.[33] Microsoft Gaming canceled Odyssey, a game Blizzard Entertainment had worked on for over 6 years and laid off some of the same staff who had worked on Odyssey.[34] Sony canceled a live service game from Naughty Dog and London Studio, resulting in layoffs at both studios.[35][36] Electronic Arts canceled an untitled Star Wars game by Respawn Entertainment, indicating a shift in focus away from licensed titles towards live service games and original IP.[37] Ubisoft canceled three previously unannounced games in January 2023, citing dismal financial results from the previous quarter.[38] Some of the newly founded AAA game development studios, such as Ridgeline Games and Deviation Games, closed down before even releasing their first video game. Ridgeline Games, founded in 2021, shut down just three years later in 2024. It was previously led by game director Marcus Lehto, who made a decision to leave Ridgeline Games. EA laid off the entire team on February 29, 2024.[39] Deviation Games shut down on March 1, 2024, just four years after its establishment in 2020.[40] The studio co-founder, Jason Blundell, left the company in 2022, and the studio canceled its new AAA live service game in 2023.[41][42] Less than two years after the studio was opened, Prytania Media closed Crop Circle Games, citing "changing consumer tastes" and "economic conditions changing due to the pandemic."[43] Smilegate Barcelona, the studio established in 2020 to develop an open-world AAA console title, shut down just 4 years after its establishment.[44] The video game tariffs imposed at the onset of the second Donald Trump presidency could contribute to increasing costs. Consumer shift [ edit ] The escalating expenses associated with video game development have prompted major gaming companies like Sony and Warner Bros. Games to pivot towards creating mobile and live service games.[45][46] Layoffs and studio closures have also impacted successful live service game companies, such as Epic Games and Bungie.[47][48] Several live service games launched in 2023 shut down within months, affecting developers and publishers alike.[49] These games, which employ a substantial portion of the industry workforce and generate significant profits, have faced challenges including rising development costs, user fatigue with monetization, and revenue declines post-COVID-19. Additionally, trends like battle royale games are maturing, and expanding franchises to mobile platforms does not always yield expected returns.[50] Sony's entry into live service gaming has encountered significant challenges and delays, resulting in the postponement of several major live service titles.[51][52] Although live service initiatives are becoming more popular, 68% of producers say their pipelines cannot support these kinds of projects.[53] Furthermore, 53% of major studios expect difficulties in handling their technical debt. 88% of developers questioned said they are looking into integrating new tools into their workflows due to the steep rise in game production expenses and complexity.[54] The market is nearing saturation, leading to increased competition for player time and higher user acquisition costs.[55][56] Post-pandemic response slowdown [ edit ] The first few months of the COVID-19 pandemic brought about a sharp increase in revenue for the gaming sector worldwide as people looked for indoor entertainment.[14] According to IDC, in 2020, revenue from mobile games climbed by 32.8% to $99.9 billion, while expenditure on digital PC and Mac games increased by 7.4% to $35.6 billion.[57] The amount spent on home console games increased significantly as well, reaching $42.9 billion, up 33.9%.[58][59] In the ensuing years, this growing pattern abruptly stopped.[60] Revenue growth from mobile gaming fell by 15% in 2021, and then fell even further in 2022 and 2023, to -3.3% and -3.1%, respectively. Sales of PC and Mac games saw a brief rise of 8.7% in 2021, a drop of 1.4% in 2022, and a rebound of 2.1% in 2023.[61] Similarly, after a surge in 2020, console game spending plateaued in 2021 with growth at 0.7%, followed by a decline of 3.4% in 2022, before returning to growth at 5.9% in 2023.[59][62] A new fad in the video game industry, metaverse, once led many investors and companies to believe that it was the future of the gaming industry.[63][64][65] Companies like Meta and Microsoft have made significant investments in this space.[66] The Metaverse has encountered challenges impacting investor expectations.[67] Meta reported significant operational losses of $13.72 billion in its Metaverse division in 2021, raising concerns among investors. Meta's acknowledgment that full realization of Metaverse products may take another 10 to 15 years tests investor patience with its long-term horizon.[68] Inflation and economic uncertainties have affected consumer behavior, delaying the adoption of Metaverse-related technologies like headsets. Meta revised its monthly active user targets downward from 500,000 by the end of 2022 to 280,000, disappointing investors with lower-than-expected engagement.[69] Mergers and acquisitions [ edit ] One of the primary reasons for layoffs in the video game industry is mergers and acquisitions. Video game companies believed that the significant growth witnessed during the pandemic would continue afterward, leading many firms to explore mergers and acquisitions.[70] Between 2020 and 2024, 16 out of the 22 most expensive video game acquisitions in video game history occurred, with major players such as Microsoft, Sony, Embracer Group, Tencent, Take-Two Interactive, and Electronic Arts each making at least one acquisition.[71] After several acquisitions, Embracer Group announced that they will undergo a significant restructuring of the company, including the closure of studios, layoffs of employees, and cancellation of dozens of video game projects.[72] Embracer Group faced a setback when a $2 billion deal with an anonymous partner fell through, later revealed to be Savvy Games Group. Savvy, owned by Saudi Arabia's sovereign wealth Public Investment Fund, had already invested $1 billion in Embracer.[73] Following the deal's collapse, Embracer announced a restructuring, including shutting down or selling studios and pausing game development. The reasons behind the deal's collapse remain undisclosed, but it was intended to establish Savvy as a major player in the gaming industry.[74] Embracer CEO Lars Wingefors had previously faced criticism for accepting investment from Savvy due to concerns about human rights violations by the Saudi government.[75] After several restructuring programs, Embracer Group reduced its headcount by 7,761, closed or divested 44 internal and external studios, and decreased the number of game projects by 80.[76][77] Several studios and publishers under Embracer Group, Sega and Microsoft Gaming have either opted to spin off from their parent companies or have been compelled to be sold off, resulting in mass layoffs. On February 29, 2024, Microsoft Gaming studio Toys for Bob revealed their decision to spin off from Activision and operate as an independent studio, while expressing openness to collaborating with both Activision and Microsoft on future projects.[78] Embracer Group announced plans to divest Saber Interactive to a private firm for $500 million.[79] On March 28, 2024, Take-Two Interactive announced its intent to acquire Gearbox Software from Embracer Group for $460 million.[80] On the same day, Relic Entertainment was sold by Sega to an unspecified investor,[81] and Thunderful Group sold Headup Games to Microcuts Holding. Headup Games was initially acquired by Thunderful for €11 million in 2021.[82] Russian invasion of Ukraine [ edit ] In February 2022 the Russian invasion of Ukraine caused an exodus of Russian studios and developers, many of which became established in Cyprus. By April, 42% of Russian developers had either already left the country or made plans to leave in the next few months.[83] Russian developers outside the country have reported difficulty in getting projects funded by publishers, as trust is low.[84] The online games market in Russia suffered an 80% decline that year, and the market collapsed in both Russia and Belarus.[85][86] Many western video game companies ceased operating in Russia, and all major Russian video game trade shows- many of which had not been held since 2019 due to the pandemic- were discontinued. This included IgroMir and Comic-Con Russia as well as several e-sports events.[87][88] Riot Games technical artist Farhan Noor hosts a website which provides tracking data for the layoffs, and this uses 2022 as the starting year for the period and includes the immediate aftermath of the invasion.[89][90] Vladimir Putin made a series of edicts over the following two years with the aim of revitalising the Russian games industry; these were ridiculed by outside observers as ineffective and impossible to fulfill. Putin effectively legalized piracy,[91] and ordered the creation of a "Russian Electronic Arts" and a game engine to compete with Unreal.[92] In 2023 he also ordered the creation of a game console on par with the Playstation 5 and Xbox in only three months.[93] Kommersant reported that such a project would take a decade, and others have noted that restrictions on importing chips to Russia would make that even more challenging. Techdirt questioned how well Putin understands the game industry given that he was 71 years old at the time of the console order.[94] Game development has continued within some Ukrainian studios during the war, though blackouts have of course disrupted operations. Nordcurrent's Dnipro office has continued development even after a bomb detonated fifty meters from the building and shattered the windows. Aurum Dust is a studio composed of a mixture of Ukrainians and Russians who are against the war, and has continued working together despite the fighting.[84] Chinese game licensing freeze [ edit ] Beginning in August 2021, the Chinese government enacted a freeze on video game approvals. This was part of a crackdown on the industry, which the government termed "moral opium", and was accompanied by new restrictions on games for under 18s. The freeze was lifted in April 2022, but in the interim was significantly costly to the Chinese industry, affecting companies such as Tencent and NetEase.[95] The freeze led to major layoffs and closures in China over the course of early 2022.[96] Major layoffs [ edit ] Embracer Group [ edit ] Embracer Group made multiple layoffs, game cancellations, and studio closures between August 2023 and March 2024 after its $2 billion deal with Saudi Public Investment Fund fell apart. The company reportedly reduced its headcount from 15,701 to 7,873; a reduction of approximately 8,000 workers or over half of their 2024 total. The group closed or divested 44 internal and external studios, and decreased the number of game projects by 80. The company later announced that it will be separated into three standalone companies by 2026.[76][77] Unity Technologies [ edit ] Unity Technologies was severely affected, and conducted six rounds of layoffs between June 2022 and February 2025. The exact size of the layoffs have not been made public, but 80LV has estimated that they amounted to 3165 to 3365 redundancies over the course of the first five rounds. The sixth round is currently of unknown scope.[97] PC Gamer has referred to the period as a "long downward spiral".[98] On January 17, 2023, Unity Technologies laid off 284 employees as part of a reassessment of objectives, strategies, and priorities in response to current economic conditions. CEO John Riccitiello explained that the layoffs were meant to reduce overlap and shelve certain projects to ensure the company's future strength.[99] Later, on November 29, 2023, Unity announced an additional 265 layoffs, constituting 3.8% of its workforce, as part of a "company reset," according to Reuters. Most of the affected workers (256) were from the Wētā Digital division, which Unity had acquired for $1.6 billion in 2021, along with several Wētā FX tools and 275 employees. On May 3, 2023, Unity announced plans to cut roughly 600 jobs, approximately 8% of its workforce. Additionally, Unity intended to reduce its global network of offices over the next few years from 58 to fewer than 30.[100] The majority of the Unity layoffs occurred in the wake of a controversial pricing change termed the "runtime fee". The policy caused community backlash and a developer boycott. A number of studios announced that they were moving away from the engine permanently in the wake of the decision,[101][102] and tools were developed to assist in porting existing projects away from Unity.[103] The incident ultimately resulted in the resignation of Unity CEO John Riccitiello,[104][105] as well as the leader of their engine division, Unity Create chief Marc Whitten.[106] Unity reduced its headcount by a further 1700 people and closed 23 offices in 2024, though it's unclear how many of those positions lost were the product of layoffs.[107] Further layoffs were announced by the company in February 2025. The scope of these are also unknown but it includes the entire Behaviour team.[108][109] Microsoft Gaming [ edit ] On January 31, 2023, as part of broader Microsoft job cuts, 343 Industries laid off 95 employees following the "disappointing" launch of Halo Infinite's multiplayer mode. Bethesda Game Studios was also reportedly impacted by the layoffs.[110] On January 25, 2024, Microsoft Gaming underwent significant restructuring, leading to 1,900 staff being laid off. As part of this process, Blizzard Entertainment's President Mike Ybarra and co-founder Allen Adham departed from the company, while Blizzard's game Project Odyssey was canceled, and major teams working on Overwatch 2 were affected. Microsoft Gaming Studios, including Toys for Bob and Sledgehammer Games, saw staff reductions of over 30%, with most layoffs occurring at Activision Blizzard.[15] On May 7, 2024, Microsoft Gaming closed three studios: Tango Gameworks, Arkane Austin, and Alpha Dog Games, and announced the merger of Roundhouse Studios into ZeniMax Online Studios. This move was part of a larger "reprioritization of titles and resources" to focus on high-impact games and new intellectual properties, resulting in the cessation of development on certain projects and the reassignment of teams within Bethesda and ZeniMax. However, Tango Gameworks was acquired by Krafton in August 2024, retaining about half of its developers and the Hi-Fi Rush property.[111] And on September 12, 2024, Microsoft Gaming CEO Phil Spencer announced that an additional 650 support and corporate roles would be eliminated.[112] On July 2, 2025, Microsoft announced more than 9000 layoffs, a portion of which was from the gaming division. This included the cancellation of various projects such as Everwild and Perfect Dark, with the closure of the studio of the latter. [113] Sony Interactive Entertainment [ edit ] On October 31, 2023, Sony Interactive Entertainment announced additional layoffs affecting around 100 Bungie employees and disclosed delays for two upcoming titles: Marathon and the Destiny 2 expansion, The Final Shape. According to Bloomberg, the layoffs came weeks after executives revealed that Bungie's revenue was 45% lower than projected, which Parsons attributed to the underperformance of Lightfall.[114] On February 27, 2024, Sony Interactive Entertainment announced the layoff of 900 employees across various studios, citing the need to restructure operations in response to the evolving economic landscape and changes in product development, distribution, and launch strategies. Layoff timelines will vary by location, and PlayStation's London Studio will be closed entirely.[17] On July 31, 2024, Sony announced further layoffs at Bungie, cutting 220 employees (17% of Bungie's workforce), while 155 employees were reassigned to other PlayStation Studios, and around 40 moved to a new studio. Bungie CEO Pete Parsons acknowledged that the company had been overly ambitious and exceeded its financial safety margins, operating at a loss.[115] On October 29, 2024, in light of the unsuccessful launch and subsequent shutdown of Firewalk Studio's live-service game Concord, Sony Interactive Entertainment announced the closure of two studios resulting in 210 layoffs.[116] Firewalk Studios closure resulted in 170 employees being laid off and the Neon Koi closure resulted in their unannounced live-service mobile game being canceled alongside the layoff of 40 employees.[117] During the first quarter of 2025, on February 14, 2025, an estimated 25 contingent workers were laid off from Bend Studio as a result of the cancellation of Bend Studio's unannounced live-service game the month prior.[118][119] This project cancellation later impacted PlayStation Visual Arts as on March 5, 2025, it was reported that an unknown number of staff were laid off. Separately, that same day, PlayStation Malaysia also underwent layoffs.[120] Electronic Arts [ edit ] On March 29, 2023, Electronic Arts laid off 6 percent of its workforce as part of a strategic shift to reevaluate its investment strategy and reduce office space, according to a blog post by EA CEO Andrew Wilson.[121] The layoffs were aimed at moving away from projects that did not contribute to EA's strategy, reviewing its real estate footprint, and restructuring some teams. While specific departments affected by the layoffs were not mentioned, efforts were made to provide opportunities for affected workers to transition onto other projects where possible.[122] On February 28, 2024, Electronic Arts (EA) announced the layoff of 670 staff members. EA's CEO, Andrew Wilson, outlined the company's focus on owned IP, sports, and massive online communities as part of its business advancement. Additionally, EA shut down Ridgeline Games and canceled a Star Wars single player game developed by Respawn Entertainment.[123][124] These cuts included 23 jobs at Respawn that were announced in March 2024.[125] An additional 300-400 layoffs took place in May 2025, resulting in the cancellation of a Titanfall game.[126] Epic Games [ edit ] On September 28, 2023, Epic Games announced a layoff affecting 16% of its workforce, or around 830 employees. The news was initially reported by Bloomberg before Epic Games published its internal memo online. CEO Tim Sweeney explained in an email to staff that the decision was due to the company's ongoing financial situation, stating that they had been spending more money than they were earning. Sweeney expressed optimism about navigating the transition without layoffs but acknowledged that it was unrealistic in retrospect."[127] Take-Two Interactive [ edit ] On April 16, 2024, Take-Two Interactive announced plans to lay off 5% of its workforce and cancel several video game projects. The company cited a cost-reduction plan, anticipating total charges of $160 million to $200 million. These measures are expected to be largely implemented by December 31, 2024.[128] Previously, Take-Two Interactive stated that they were working on "significant cost reductions" but stated they had no current plans for layoffs.[129] Riot Games [ edit ] On January 22, 2024, Riot Games announced a significant restructuring, leading to the layoff of 530 employees, which accounts for about 11% of the company's total workforce. The company also shut down Riot Games' indie publishing label, Riot Forge. The decision was made as part of Riot's strategy to refocus on fewer, high-impact projects, aiming for a more sustainable future.[130] List of major layoffs [ edit ] Canceled major AAA video games [ edit ] Reactions [ edit ] Media outlets [ edit ] Some media outlets compared the 2023-2024 layoffs to the video game crash of 1983, when the US video game market collapsed due to an oversaturation of poorly made, low-quality games, causing the video game industry to enter a recession for two years. This has sparked discussions about a potential "second video game crash."[168][169] Windows Central's article titled "Embracer Group is a prime example of bad consolidation" criticized Embracer Group for its frequent layoffs, studio closures, and personnel cuts. The closure of Volition Studios, layoffs at Lost Boys Interactive, and the shutdown of Free Radical Design are highlighted as notable incidents.[170] Publishers [ edit ] Both Microsoft and Sony have acknowledged that the current approach cannot continue and are exploring alternative business models. Microsoft Gaming CEO Phil Spencer addresses the stagnation in the gaming industry, recognizing its repercussions on job cuts and the challenging decisions faced by companies. He underscores the importance of industry expansion for long-term sustainability, advocating for a shift towards enlarging the player base rather than solely concentrating on extracting revenue from existing players. By prioritizing the growth of Xbox through attracting new players and nurturing creators, Phil aims to guarantee enduring strength and prosperity for the platform and the industry overall.[171][172] When asked about the gaming layoffs, Phil Spencer addressed both the broader industry trend and the unique aspects related to Xbox's current business. Spencer expressed concern over the lack of growth in the industry, highlighting the pressure on publicly traded companies to show growth to investors.[173] This scrutiny often leads to cost-cutting measures when revenue growth is stagnant. Spencer emphasized the need for the industry to focus on regaining growth to ensure job security and career opportunities for professionals. Regarding Xbox's strategy, he discussed the importance of exclusivity and expanding the player base by making games available on multiple platforms.[174] Spencer stated that every decision made by Xbox is aimed at strengthening the brand in the long run, even if not everyone agrees with those decisions. Spencer also touched on the evolving nature of Xbox, stating that the brand is moving away from traditional exclusivity models to adapt to the preferences of younger audiences. Spencer emphasized that Xbox aims to be a platform where players can find the games they want, regardless of the device they use, aligning with the accessibility and cross-platform trends seen among younger gamers.[175] Sony Interactive Entertainment chairman Hiroki Totoki stated that he acknowledges the need to manage development costs better in PlayStation Studios, recognizing industry-wide challenges like rising expenses and lengthy schedules.[176] Totoki emphasizes sustainable profitability and transparently addressing challenges while highlighting the significance of first-party titles achieving growth across platforms.[177][178] Wes Keltner, CEO of Gun Interactive, expressed concern about the shrinking space for creative and innovative ideas from small game development teams. Keltner noted a lack of funding for indie projects, leading to promising ideas being abandoned at the prototype stage. Keltner highlighted the trend of mergers and acquisitions (M&A) leading to larger studios but diminishing creative freedom. He emphasized the notion that risk is a driving force behind creativity in the gaming industry.[179][non-primary source needed] Game developers [ edit ] In response to layoffs in the gaming industry, developers expressed a mixture of frustration, disillusionment, and concern about the future.[180] Many felt blindsided by the layoffs, especially when they were told the reasons were related to underperforming games or unsustainable costs.[181] Some developers pointed out the disconnect between management decisions and the realities of game development, such as over scoping projects or investing in risky technologies without clear strategies. There was also criticism of how layoffs were handled, with some developers feeling that companies prioritized executive salaries and unnecessary expenses over investing in game development.[182] There were instances where studios spent extravagantly on events or office perks shortly before laying off a significant portion of their workforce, leading to feelings of betrayal among employees.[4] Developers highlighted broader industry trends contributing to the instability, such as the increasing reliance on outside investors and shareholders who prioritize short-term profits over long-term sustainability. The pandemic exacerbated these issues but was not solely responsible for the ongoing wave of layoffs. Overall, developers expressed deep concern about the future of the industry and the toll these layoffs were taking on morale and creativity. Many feared that the current instability could have long-lasting consequences for both individuals and the industry as a whole.[182][183] At Game Developers Conference 2024, Epic Games staff organised a "GDScream", where a large number of developers gathered in a park to scream at the sky in "a moment of pure catharsis". The trade show more broadly featured many speeches from award winners about the state of the industry.[184] Dinga Bakaba, the studio head of Arkane Lyon, publicly criticized Microsoft Gaming executives for their decision to close several studios. He emphasized the importance of taking care of artists and entertainers in the video game industry, highlighting that their role is to create value for corporations.[185] Amir Satvat [ edit ] On December 12, 2024, the Game Awards 2024 introduced the inaugural Game Changer Award, which was presented to Amir Satvat. He was recognized for his efforts in assisting individuals affected by job loss by helping them find new opportunities. The presentation of the award received a standing ovation and was noted as one of the most significant moments of the event.[186][187] In 2025, Satvat received the Giving Award from Games for Change, an honor recognizing individuals, companies, or organizations making meaningful contributions to the community through initiatives such as fundraising, scholarships, and career support.[188] He was also honored with the inaugural Industry Impact Award from Game Dev Heroes for helping thousands find work during one of the industry’s most difficult periods.[189] Future [ edit ] Unionization [ edit ] Unions are relatively rare in the video game industry. But after several public scandals involving abuse, sexism, layoffs, and overwork, some game workers have developed a keen interest in organization in the last few years.[190] After starting the process in April, employees at Sega of America's Irvine, California headquarters filed to become unionized with the Communications Workers of America on July 10, 2023. In July, the union election was successfully won by the Allied Employees Guild Improving Sega (AEGIS), with 91 votes in favor and 26 votes against. More than 200 positions in a range of areas, such as marketing, games as a service, localization, product development, and quality assurance, will be covered by the union.[191] On October 6, 2023, Over 100 developers at Avalanche Studio Group unionized.[192] After experiencing layoffs, some workers at CD Projekt Red formed a union on October 9, 2023.[193] According to the union, these layoffs caused significant stress and insecurity among workers, leading to the need for better protection and representation. The union aims to provide more security, transparency, and a stronger voice for workers in times of crisis, believing that mass layoffs pose a threat to the gaming industry and that unionizing is crucial for preserving its potential. The union said its priority was to give CD Projekt Red staff a voice in company decision-making, with a view to increasing employment stability. It also wants to help workers' voices be heard on working conditions "in the long run."[194] On December 5, 2023, 300 Quality assurance workers at ZeniMax Media announced that they were organizing a union.[195] Additionally, a labor neutrality agreement was announced in June 2023 by Microsoft and the Communication Workers of America (CWA). Under this deal, Activision Blizzard employees were entitled to freely form a union, and Microsoft promised to acknowledge and support that union.[196] On March 8, 2024, 600 workers from Activision's QA team joined CWA, establishing the largest game developer union in North America.[197] Growth [ edit ] Despite the layoffs, studio closures, and cancellations of video game projects, as well as high inflation, the video game market continues to remain robust.[198] Many investors and industry analysts believe that the video game industry will fully recover in 2025 and 2026 with major releases like Grand Theft Auto VI, Monster Hunter Wilds, Ghost of Yōtei, Doom: The Dark Ages, Pokemon Legends Z-A, and others.[20][199] Investors also expect Nintendo to release its new hardware, which will boost video game sales and revenue.[200] Executive Director of Circana (The NPD Group), Mat Piscatella, stated that consumer demand remains strong, but consumers are under pressure due to economic challenges. Some parts of the industry are already growing and in a healthy position, like mobile, and Piscatella believes that other segments will follow suit in 2025.[201] According to a 2024 PwC report, the global gaming industry is expected to reach a value of $321 billion by 2026.[202] Deloitte predicts that the share of theatrical box office revenues from video game intellectual property (IP) will double by 2025. Additionally, most major video streaming platforms are expected to include shows based on popular games.[203] Another report by GlobalData suggests that the video games market could become a $300 billion industry by 2025. Factors contributing to this growth include mobile gaming and innovative offerings.[204] Bain & Company predicts that global gaming revenue could surge by over 50% in the next five years.[205] Mobile video games began growing in 2024, with U.S. mobile gamers spending over $28 billion that year. This marked a recovery for the industry after a two-year economic slowdown, surpassing the previous record set in 2021.[206] Monopoly Go was the highest-grossing mobile game, and Call of Duty: Black Ops 6 led in console sales. Monopoly Go generated $2.7 billion alone.[207] U.S. consumer spending on video games totaled $58.7 billion in 2024.[208] Juniors and long term effects [ edit ] The layoffs affected junior staff in greater numbers than other skill levels, and in some cases juniors were specifically targeted.[209][210] As the industry was recruiting too few juniors to begin with, there are long term concerns for skills development, diversity, and the viability of the games industry as a career path for young developers.[211] The layoffs were demoralising for juniors, and around a third of those who were laid off left the industry entirely.[211][212] A level designer interviewed by PC Gamer commented that "As a Junior who put blood, sweat, and tears into obtaining my first role in the industry, I am now back again going in circles looking for roles that are junior level (which is non-existent as every job posting I see is either Senior, Principal, or Lead)."[213] The number of junior positions available has been low for years, but fell dramatically during the period. In 2022, 9.4% of available games jobs in the United Kingdom were at the junior level.[214] By 2023 this had fallen to 2.9%, with only 34 junior positions nationwide over the year.[215] The junior figure had partially recovered to 7% by 2024, but there were no apprenticeships sector wide for the entire year.[216] The few junior jobs available are fiercely competed for; XR Games advertised for four junior positions in 2024 and received 18,000 applications.[217] Grads in Games, a major route into the industry for juniors in the UK, was placed on hiatus in 2024 due to the lack of entry level hiring. Industry support for the program had been in place for a decade but now "just doesn't exist".[218] The industry's failure to hire and train new workers is exacerbating existing skills shortages at the senior level, as there are not enough staff progressing through the field and moving up to higher positions.[215] A developer interviewed by DigiDay remarked that by recruiting only existing senior level talent, there may be "no new generation of seniors."[211] In the UK in particular, the first wave of developers are now starting to retire, leaving fewer senior staff to train any new juniors.[216] The current skills structure in the UK games industry is unsustainable.[219] As juniors are more likely to be women or from minority groups such as LGBT demographics, this practice has also had a negative effect on diversity in the industry.[211][220] See also [ edit ]
2022-12-01T00:00:00
https://en.wikipedia.org/wiki/2022%E2%80%932025_video_game_industry_layoffs
[ { "date": "2022/12/01", "position": 3, "query": "AI layoffs" } ]
AI is taking our jobs. again. : r/DataScienceMemes
The heart of the internet
https://www.reddit.com
[]
r/breakinglayoffs. • 2 mo. ago. AI was able to replace 40% of employees · r/breakinglayoffs - AI was able to replace 40% of employees. 91 upvotes · 32 ...
Create your account and connect with a world of communities. New to Reddit? By continuing, you agree to our and acknowledge that you understand the
2022-12-01T00:00:00
https://www.reddit.com/r/DataScienceMemes/comments/zp1y4h/ai_is_taking_our_jobs_again/
[ { "date": "2022/12/01", "position": 7, "query": "AI layoffs" } ]
Elastic Announces Layoffs With Q2 Earnings; Hundreds Of ...
Elastic Announces Layoffs With Q2 Earnings; Hundreds Of Workers Cut
https://www.crn.com
[ "Wade Tyler Millward" ]
Elastic Announces Layoffs With Q2 Earnings; Hundreds Of Workers Cut. By ... The 10 Hottest Agentic AI Tools And Agents Of 2025 (So Far) · The HPE-Juniper ...
Elastic Announces Layoffs With Q2 Earnings; Hundreds Of Workers Cut ‘I didn‘t take this decision lightly,’ Elastic CEO Ash Kulkarni says in a post online. Enterprise search and cybersecurity tools vendor Elastic plans to reduce its workforce by about 13 percent, eliminating hundreds of employees, the company announced during its latest quarterly earnings call and in a regulatory filing Wednesday. Mountain View, Calif.-based Elastic is the latest company to shed workers amid high inflation in the United States and concerns of a recession next year. CRN has reached out to Elastic for comment. id unit-1659132512259 type Sponsored post [RELATED: Tech Layoffs In 2022: 23 Companies Slashing Their Workforce] Elastic Announces Layoffs Alongside Q2 Earnings In an online post, Elastic CEO Ash Kulkarni said that “the vast majority” of affected employees were notified and that the company will pay for a minimum of 14 weeks of severance, an additional week per completed full year of service and six months of existing health care premiums, among other payments. The company will also provide resume and job search support plus immigration support, he said. “I didn’t take this decision lightly,” Kulkarni said. “Since becoming CEO, I have had the opportunity to spend time with Elasticians around the globe. It’s been an honor getting to know so many of you. Your passion and commitment humble me.” He continued: “We are fortunate that security, observability, and search are mission-critical to our customers. However, it has become clear that the global macroeconomic environment is forcing our customers to tighten budgets and review investments more closely. This is especially true in certain segments of the market like small and medium businesses where the current appetite to spend in uncertain times is limited.” In June, the company reported having about 3,000 employees. Elastic operates in 45 countries. The company has a partner program for regional partners, channel partners, resellers, managed service providers (MSPs), original equipment manufacturers (OEMs), global systems integrators (GSIs) and other business types. In its regulatory filing, Elastic said it plans to implement “certain facilities-related cost optimization actions” in addition to cutting workers. The employee severance and termination costs will reach between $25 million and $28 million. Total charges under the restructuring plan will reach $32 million to $36 million. Most of the charges will come in the third quarter of fiscal year 2023 – a quarter that ends Jan. 31. The workforce and office space reductions will finish by the first quarter of fiscal year 2024. Employees took to LinkedIn to confirm their leave from Elastic. Affected roles included a global lead product marketer, a sales development representative, account executives and a regional marketer. “It still feels like I wasn’t in the right place at the right moment or that this is all a big misunderstanding,” an Elastic SMB account executive for Canada wrote on LinkedIn. “It’s even harder to deal with this news when literally a minute before I was celebrating my success.” Employees from companies including Fastly, Confluent and Arctic Wolf posted about job openings for affected Elastic workers. Elastic Q2 Earnings Meanwhile, the company reported earnings Wednesday for the second quarter of its 2023 fiscal year – a quarter that ended Oct. 31. The reduction in workforce and office space comes despite total revenue of $264.4 million, up 34 percent ignoring foreign exchange. Elastic Cloud revenue was $103.2 million, up 52 percent year over year. The company had an operating loss of $49 million following generally accepted accounting principles (GAAP). The company had $856.2 million in cash on Oct. 31. Following the company’s own accounting principles, Elastic saw operating income of $4.9 million and an operating margin of 2 percent. The goal is to reach 10 percent operating margin under these accounting principles next fiscal year, according to a company statement. Elastic reached 19,700 total subscription customers and more than 1,050 customers with annual contract value (ACV) above $100,000. The company continued to develop partnerships with Google Cloud, Microsoft Azure and Amazon Web Services, according to a statement. Elastic expects total revenue for the third quarter of the 2023 fiscal year – a quarter that ends Jan. 31 – to reach between $272 million and $274 million. The company expects total revenue for the current fiscal year to reach about $1 billion, according to a statement. Kulkarni said on the earnings call Wednesday that he has “continued confidence in our long-term market opportunity and the core fundamental strengths of our business,” according to a call transcript. “During the quarter, we continue to make progress across our three key focus areas: driving durable growth, widening our competitive moat, and continuing our focus on profitable growth,” he said. “We also saw our customers continue to show preference for consolidation onto our platform for multiple use cases.” Despite this, in October, small and midsize business (SMB) customers slowed consumption and tightened their spending, with more deal scrutiny, he said. Customers in countries especially hit by a strengthening U.S. dollar were especially hit, he said, according to the transcript. “That effort that‘s being spent on the SMB area is really not giving us commensurate returns,” Kulkarni said. “And we are not expecting the SMB environment to change either in the near future. We expect that that’s going to be an area where there will be continued stress in the economy. On the other hand, we continue to see on the enterprise side long-term opportunity for us to continue to do well.” Along with reduced headcount, the company is investing in more self-service and automation for SMB customers, he said. The company will hire more technicians with cloud and serverless experience. During the earnings call, Janesh Moorjani, Elastic’s chief financial officer and chief operating officer, said that customer appetite for cloud over on-premises did not change with the uncertain economy. Elastic’s stock traded at $57.13 Thursday afternoon Eastern time, down about 7 percent from market close Wednesday.
2022-12-01T00:00:00
https://www.crn.com/news/cloud/elastic-announces-layoffs-with-q2-earnings-hundreds-of-workers-cut
[ { "date": "2022/12/01", "position": 49, "query": "AI layoffs" } ]
Gannett initiates another round of layoffs, cutting its news ...
Gannett initiates another round of layoffs, cutting its news division by 6%
https://www.poynter.org
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Gannett started another round of layoffs Thursday, just four months after the company terminated hundreds of employees. ... AI is creeping into every space of our ...
Gannett started another round of layoffs Thursday, just four months after the company terminated hundreds of employees. The layoffs, which will continue into Friday, are part of Gannett’s efforts to cut its news division staff of 3,440 by 6%. That amounts to roughly 200 layoffs. News division head Henry Faure Walker first warned journalists about impending layoffs on Nov. 17. He wrote in an email to staff that Gannett’s news division costs are too high and that the company needed to enter the new year in a “stronger economic position.” Gannett is the largest newspaper chain in the country with more than 200 dailies. Faure Walker’s November email mentioned that Gannett was taking “similar actions” in its other divisions. Spokesperson Lark-Marie Anton confirmed Thursday that other divisions are also undergoing reductions, but the majority of individuals impacted during this week’s cuts are part of the news organization. She declined to answer questions about which papers and positions have been affected. “While incredibly difficult, implementing these efficiencies and responding decisively to the ongoing macroeconomic volatility will continue to propel Gannett’s future,” Anton wrote in an emailed statement. Journalists started to receive notices Thursday morning. Among those affected were reporters at flagship paper USA Today and producers working on Gannett’s digital optimization team. Gannett intends to eliminate all of its DOT regionals, according to an email the company sent to the Atlantic DOT Guild, the union representing producers on the Atlantic team. Though the teams will not be dissolved until Dec. 9, Gannett has already started laying off DOT employees. Fifty of 125 total employees were notified Thursday that their positions had been eliminated. Many of those employees received notice of their layoff prior to the mid-morning meeting Gannett holds every day for its DOT. Atlantic DOT Guild unit chair Jack McLoone estimated that the majority of attendees at Thursday’s meeting had been laid off. “It just became a very emotionally charged situation,” he said. Digital producers at Gannett used to work for individual newsrooms, but in 2018, the company restructured and started creating regional teams. Many employees had to reapply for jobs on these new teams. Now, Gannett appears to be reverting to its original structure. Current DOT employees who are not reabsorbed into individual newsrooms will be laid off, according to the email sent to the Atlantic DOT Guild. Anton wrote in an email that Gannett is dissolving the DOT to prioritize “maintaining reporting resources in our newsrooms.” “While the DOT will no longer exist as a centralized function, digital producers will continue to work with newsrooms across the USA TODAY Network,” Anton wrote. Because the Atlantic Digital Optimization Team is unionized, Gannett will have to bargain over the changes with the union. Other DOT regionals are not as lucky. Producers at the Midwest DOT announced Oct. 20 that they were unionizing as the Midwest Digital Guild. Because Gannett refused to voluntarily recognize the union, Midwest DOT employees had to vote in a National Labor Relations Board election to get their union certified. The NLRB was supposed to mail them their ballots Thursday, but 9 of the 14 producers were laid off. “Our ballots for unionizing were to be mailed today by the NLRB, but it’s looking like our work group will be demolished,” the Midwest News Guild wrote in an email. “Our guild is investigating all possible avenues to respond to this devastating news.” The Atlantic DOT Guild emailed Gannett’s outside counsel Thursday to bargain over the changes but received an out-of-office message, McLoone said. DOT employees help craft headlines, assemble newsletters, optimize articles for search engines, send push alerts and design social media graphics, among other responsibilities. McLoone said eliminating those positions will make it more difficult for readers to find the news. “So much of our job is trying to break through the wider noise of the internet,” McLoone said. “Gannett likes to talk all the time about how they’re a digital-first company. … But now they’re cutting the knees out from the people that were in charge of actually pushing stories and tracking metrics and making sure we were reaching subscription goals.” This week’s layoffs are the third round of cuts at Gannett in six months. In August, the company laid off 400 people and eliminated another 400 open positions. Gannett then announced another round of cuts in October including buyouts, a hiring freeze and the suspension of company contributions to employee 401(k) accounts. Employees also will be required to take a week of unpaid leave over the holidays. These measures have come after two straight quarters of disappointing financial results. Gannett reported $54 million losses during both the second and third quarters. CEO Mike Reed has told analysts on earnings calls that he does not expect revenue to rebound until 2024. Correction, Dec. 2, 2022: This article was updated to correct the year Gannett created its digital optimizaiton team. The DOT started in 2018, and additional regional teams were added in the following years.
2022-12-01T00:00:00
2022/12/01
https://www.poynter.org/business-work/2022/gannett-initiates-another-round-of-layoffs-cutting-its-news-division-by-6/
[ { "date": "2022/12/01", "position": 65, "query": "AI layoffs" } ]
CNN lays off hundreds of staffers − read the memo
CNN lays off hundreds of staffers after business review − read the memo
https://www.cnbc.com
[ "Alex Sherman", "In Alex-Sherman" ]
AI · Enterprise · Internet · Media · Mobile · Social Media · CNBC Disruptor 50 · Tech ... The layoffs affected hundreds of staffers, but amounted to a "single- ...
Licht sent a memo to all staffers Thursday afternoon after the news was delivered to employees, which included long-time HLN anchor Robin Meade and reporter Chris Cillizza. Licht wrote in the memo he will hold a town hall next week to answer any questions. Licht's cuts are part of a broader effort at Warner Bros. Discovery, the parent company of CNN, to cut costs heading into 2023. Read the full memo here: December 1, 2022 To my CNN colleagues, As promised in my note yesterday, I am following up with an overview of the changes we have made across the company. Our goal throughout the strategic review process has been to better align our people, processes and resources with our future priorities, strengthen our ability to deliver on CNN's core journalistic mission and enable us to innovate in the years ahead. At the highest level, the goal is to direct our resources to best serve and grow audiences for our core news programming and products. To achieve these goals, we will be reducing open job positions, reimagining our workflows and aligning our staffing, investments and focus around three key strategic priorities: programming, newsgathering and digital. All decisions are designed to strengthen the core of our business. While it is not possible to capture every impacted role in an email like this, I want to walk through the broader changes we are making: HLN Beginning December 6, CNN will no longer produce live programming for HLN and instead will simulcast CNN This Morning. HLN Crime programming will move under the WBD Networks led by Kathleen Finch and will be merged with ID. I want to take a moment to thank Robin Meade— she is not only an exceptionally popular anchor, but also one of the longest-running morning hosts in history. I know the HLN audience will miss her and the other HLN talent. CNN International CNN International is reorganizing some of its teams and bureaus, and effective immediately, the 5:00-5:30pm ET show will be replaced by a simulcast of CNN US for that half hour. CNN en Español CNNE's linear network will seek to expand its audience by diversifying the network's programming beyond news. We will continue to produce news for CNNE, and throughout next year, we will look to develop a far more robust digital platform for CNNE with the aim of launching it in 2024. We believe that investment will better serve and significantly grow our Spanish-language news audience, and we will have more to share on that in 2023. U.S. Newsgathering We are restructuring across some of our beats, realigning resources to staff up in some units and in more areas around the country. This will help us deliver on our goal of covering the United States more broadly. Many of the staff reductions in Newsgathering will be offset by the addition of new roles to best serve our audience across platforms. Contributors We are also shifting our approach to paid contributors. In some areas, we will rely more on our CNN journalists. Overall, we will engage contributors who are subject-matter experts that expand and diversify the viewpoints we bring our audience. Programming Our programming teams will see some reductions in show staffs and, in some cases, the combination of teams for our dayside and weekend lineups. Creative Marketing The Creative Marketing team will see an overall reduction in size, realigning around in-house production and consolidating creative and strategy roles in New York. Roles will be added to both support that work and expand our digital and growth marketing efforts. Research Research is reorganizing to focus resources on CNN's core businesses and to optimize our recently integrated Digital Analytics and Data Science teams. Operations The Operations teams are restructuring to align with the changes to other units across the organization. CNN Digital CNN Digital conducted an exercise earlier this fall to ensure they were best structured for the future. They made changes then and, as a result, there are no further impacts in this process. The changes we are making today are necessary and will make us stronger and better positioned to place big bets going forward without fear of failure. To our departing colleagues, I want to express my gratitude for your dedicated and tireless service and for your many contributions to CNN. To all employees, I want to underscore the importance of taking the time you need to best be able to move forward. You can find resources to support you now here. I will be holding a town hall on Tuesday to answer your questions, which can be submitted anonymously here. I am proud of this CNN team, and together we will ensure CNN continues to be the world's most vital source of news and information. Chris
2022-12-01T00:00:00
2022/12/01
https://www.cnbc.com/2022/12/01/cnn-lays-off-hundreds-of-staffers-read-the-memo.html
[ { "date": "2022/12/01", "position": 70, "query": "AI layoffs" } ]
Gannett Starts Another Round of Staff Cuts
Gannett Starts Another Round of Staff Cuts
https://www.nytimes.com
[ "Benjamin Mullin" ]
The layoffs are the latest in a series of cost-cutting measures by Gannett ... Artificial Intelligence. Newsletters. DealBook. The most crucial business ...
Gannett, the largest newspaper chain in the United States, began another round of layoffs Thursday, joining a host of other media companies cutting jobs in recent weeks. Employees at Gannett’s newspapers, which include USA Today, The Indianapolis Star and The Detroit Free Press, began receiving layoff notifications Thursday, part of an effort to cut about 6 percent of the company’s roughly 3,440-person U.S. media division. Word of the notifications spread quickly among Gannett employees. At USA Today, journalists received invitations on their employee calendars to join meetings with editors and human resources representatives. The layoffs are the latest in a series of cost-cutting measures by Gannett, which in August eliminated about 400 jobs and said it would not fill hundreds of open positions. More spending cuts were announced in October, when Gannett’s chief executive, Mike Reed, told employees that the company would offer voluntary buyouts and require workers to take unpaid leave.
2022-12-01T00:00:00
2022/12/01
https://www.nytimes.com/2022/12/01/business/media/gannett-layoffs.html
[ { "date": "2022/12/01", "position": 75, "query": "AI layoffs" } ]
CNN informs employees that layoffs are under way
CNN informs employees that layoffs are under way
https://www.rappler.com
[ "Michelle Abad" ]
Is The Philippines Ready For AI? The Future Depends On It · Sandiganbayan · 4 former officials of Philippine Tourism Authority convicted of graft · RAPPLER.
This is AI generated summarization, which may have errors. For context, always refer to the full article. CNN. In this file photo, the CNN logo stands outside the venue of the second Democratic 2020 US presidential candidates debate, in the Fox Theater in Detroit, Michigan, USA, on July 30, 2019. The job cuts have been anticipated and come at a time when companies are looking to rein in costs and trim their headcount to brace for an economic slowdown Warner Bros. Discovery-owned CNN’s top boss Chris Licht informed employees in an all-staff memo on Wednesday, November 30, that layoffs are under way, according to an email seen by Reuters. Licht said CNN would notify a limited number of individuals, largely some of its paid contributors on Wednesday and the impacted employees on Thursday, according to the memo. He would follow up with more details on the changes on Thursday afternoon. “I know these changes affect both our departing colleagues and those who remain,” Licht wrote. “And we have resources to support you.” The job cuts have been anticipated and come at a time when companies are looking to rein in costs and trim their headcount to brace for an economic slowdown. In October, Licht had warned CNN would be undergoing changes, citing “widespread concern over the global economic outlook.” The changes would affect “people, budgets and projects,” Licht had said. Cable channels operator AMC Networks on Tuesday said it would cut 20% of its US staff as it faces industry pressures and a challenging economy. – Rappler.com
2022-12-01T00:00:00
2022/12/01
https://www.rappler.com/business/cnn-informs-employees-layoffs-under-way-november-2022/
[ { "date": "2022/12/01", "position": 79, "query": "AI layoffs" } ]
IBM Common Stock (IBM) Stock Price & News
IBM Common Stock (IBM) Stock Price & News
https://www.google.com
[]
Business Today. 1 month ago. Tech layoffs 2025: IBM lays off 8,000 employees as AI replaces HR department. Financials. Income Statement.. Quarterly. Annual.
International Business Machines Corporation, nicknamed Big Blue, is an American multinational technology company headquartered in Armonk, New York, and present in over 175 countries. It is a publicly traded company and one of the 30 companies in the Dow Jones Industrial Average. IBM is the largest industrial research organization in the world, with 19 research facilities across a dozen countries; for 29 consecutive years, from 1993 to 2021, it held the record for most annual U.S. patents generated by a business. IBM was founded in 1911 as the Computing-Tabulating-Recording Company, a holding company of manufacturers of record-keeping and measuring systems. It was renamed "International Business Machines" in 1924 and soon became the leading manufacturer of punch-card tabulating systems. During the 1960s and 1970s, the IBM mainframe, exemplified by the System/360 and its successors, was the world's dominant computing platform, with the company producing 80 percent of computers in the U.S. and 70 percent of computers worldwide. Wikipedia
2022-12-01T00:00:00
https://www.google.com/finance/quote/IBM:NYSE?hl=en
[ { "date": "2022/12/01", "position": 80, "query": "AI layoffs" } ]
Layoff gloom to end next year? Job cuts by startups, digital ...
Layoff gloom to end next year? Job cuts by startups, digital companies to taper off by mid-2023, forecast experts
https://www.financialexpress.com
[ "Salman Sh" ]
Hiring, hiring news, hiring trends, job cuts, job loss, layoffs, The ... AI, tier-2 markets, omnichannel to drive next phase of growth, reveals Meta ...
The rising number of layoffs by startups and digital platforms is expected to slow down by mid-2023, hiring experts told FE. By the middle of next year, companies in the digital space may go back to hiring to fuel their growth plans, they said. Further, employees who may have been laid off by startups but possess skills in niche areas stand a good chance to get hired by MNCs across other IT domains in industries like insurance, banking, finance, and others. Also Read: Dailyhunt fires 5% of its 3,000-strong workforce, initiates 11% pay cuts for few employees “Startups in India still have a very large workforce with high attrition of around 25-30%. This means even as they cut back on jobs, many will continue to hire to fill attrition. With the next academic year, fresher hiring will be back in full swing, especially among startups…and I expect layoffs to slow down fully by the first quarter of the next financial year,” Sekhar Garisa, CEO, Monster India, said. “During economic slowdowns, large MNCs usually turn to offshore hiring in countries like India for talent. Hence, niche skilled employees stand a good chance to find new jobs,” Ashish Gupta, co-founder and CEO of Benori Knowledge, which offers consulting services to startups, said. Garisa pointed out that around 500,000 job listings are currently live on the hiring platforms are in fact from tech startups looking to hire. However, perks and salary expectations have levelled off compared with the pre-Covid era. According to him, another emerging trend could be of mid-career employees beginning to opt for upskilling to get into niche roles, where demand would rise but supply may not be adequate. Also Read: Job creation slows again after uneven recovery “There are currently 25,000 jobs for data analysts on the master platform. Upskilling courses offered by edtechs and others are expected to fill in this gap, since most of these course providers are successful in providing better compensation or a better job,” he added. The tech industry, including Big Tech and startups, together have laid off over 16,000 employees in the current calendar year so far. Many of these include unicorns, late-stage firms and even early-stage startups that were unable to raise crucial cash amid the funding crunch. The consumer internet segment currently remains the most affected in terms of job cuts. Startups in edtech, fintech, hyperlocal delivery, insurtech, content and gaming, logistics and online commerce are some of the worst affected. According to some estimates, edtech was the worst affected with 14 edtech startups laying off 6,898 employees in 2022.
2022-12-01T00:00:00
https://www.financialexpress.com/business/industry-layoff-gloom-to-end-next-year-job-cuts-by-startups-digital-companies-to-taper-off-by-mid-2023-forecast-experts-2897228/
[ { "date": "2022/12/01", "position": 83, "query": "AI layoffs" } ]
CNN lays off hundreds of staff
CNN lays off hundreds of staff
https://www.poynter.org
[ "Angela Fu", "Angela Fu Is A Reporter For Poynter. She Can Be Reached At Afu Poynter.Org", "On Signal At", "On Bluesky", "Angelanfu.Bsky.Social", "On Twitter", ".Wp-Block-Co-Authors-Plus-Coauthors.Is-Layout-Flow", "Class", "Wp-Block-Co-Authors-Plus", "Display Inline" ]
Thursday's layoffs would then target full-time employees. Axios reported ... From viral shrimp messiahs to fake news popes, AI is warping how we see the world — ...
CNN executed a round of layoffs Wednesday and Thursday, eliminating hundreds of positions including a number of on-air correspondents. Among those let go were politics reporter Chris Cillizza; correspondents Alexandra Field, Martin Savidge and Alison Kosik; and vice president of northeast news Mary Anne Fox, according to Variety. It is unclear exactly how many employees were let go. CEO Chris Licht told staff Wednesday that a limited number of people, mostly paid contributors, would be given pink slips that day. Thursday’s layoffs would then target full-time employees. Axios reported that “a couple hundred” staff would be affected. CNN has roughly 4,000 employees. Spokesperson Lauren Cone did not respond to a request for comment. Cable news channel HLN was hit particularly hard, Variety first reported. HLN was first launched in 1982 as CNN2 and later became known as CNN Headline News. However, in recent years HLN has reduced its live programming and instead focused on true crime shows. Now, CNN will stop live programming altogether for HLN on Dec. 6 and will replace “Morning Express” with a simulcast of “CNN This Morning.” In a memo to employees Thursday, Licht outlined several other changes including restructurings affecting CNN International, U.S. newsgathering operations and programming teams. CNN will also reduce open positions. Licht warned about impending layoffs in October when he wrote to staff that the company is bracing itself for an economic downturn. He said CNN would try to minimize impacts on its newsgathering operations. “There is widespread concern over the global economic outlook, and we must factor that risk into our long-term planning,” Licht wrote at the time. “All this together will mean noticeable change to this organization.” CNN has had a tumultuous year. The network started off 2022 under Jeff Zucker, who unexpectedly resigned as president in February. CNN’s owner, WarnerMedia, then merged with Discovery in April to form Warner Bros. Discovery. Lack of support from Warner Bros. Discovery then helped hasten the demise of CNN’s streaming service, CNN+, which shuttered three weeks after it launched. Hundreds of people were laid off. Licht took over in May, promising to avoid the “extremes” of cable news. He also said he would work to incorporate more conservative viewpoints. In the months since, there have been a number of high-profile departures including Reliable Sources host Brian Stelter, legal affairs analyst Jeffrey Toobin and White House correspondent John Harwood.
2022-12-01T00:00:00
2022/12/01
https://www.poynter.org/business-work/2022/cnn-lays-off-hundreds-of-staff/
[ { "date": "2022/12/01", "position": 87, "query": "AI layoffs" } ]
CNN Lays Off Hundreds of Staffers, Halts Live ...
CNN Lays Off Hundreds of Staffers, Halts Live Programming on HLN
https://www.yahoo.com
[]
... layoffs and restructuring the outlet is undergoing. “I know the HLN audience ... Ford CEO Jim Farley warns AI will wipe out half of white-collar jobs ...
CNN on Thursday laid off hundreds of staffers and made other sweeping changes that CEO Chris Lictht admitted was a “gut punch” to the network. Among the biggest changes: All live programming on HLN will be halted starting on Dec. 6. Licht singled out the work of Robin Meade, the “Morning Express” anchor who has been with HLN since 2001. In place of her show, CNN’s longtime sister channel will instead simulcast “CNN This Morning.” HLN crime programming will move under Warner Bros. Discovery Networks and will be led by Kathleen Finch as it merges with ID. “I want to take a moment to thank Robin Meade — she is not only an exceptionally popular anchor, but also one of the longest-running morning hosts in history,” Licht wrote in a staff memo outlining the layoffs and restructuring the outlet is undergoing. “I know the HLN audience will miss her and the other HLN talent.” Advertisement Advertisement Advertisement Advertisement CNN did not immediately respond to TheWrap’s request for clarification on if Meade will stay at the network following this change. Also Read: CNN CEO Chris Licht Begins First Round of Anticipated Layoffs Among other on-air talent that has been let go in the latest round of staff cuts is Chris Cillizza, Alison Kosik, Martin Savidge, Alexandra Field, and Sonia Moghe, according to CNN media reporter Oliver Darcy, who said that the number of layoffs was in the “hundreds.” The change to HLN, which was once known as CNN Headline News, marks yet another shakeup at CNN since Licht took over the network in the spring, as the network undergoes layoffs and restructuring. Advertisement Advertisement Advertisement Advertisement CNN International has also been impacted by the most recent changes, with the 5:00-5:30 p.m. ET show being replaced by a simulcast of CNN U.S. for that half hour, effective immediately. Licht also mentioned some less tangible structural changes, including “restructuring across some of our beats, realigning resources to staff up in some units and in more areas around the country,” which the CEO says will help “deliver on our goal of covering the United States more broadly.” Also Read: Don Lemon Tells Colbert CNN Was Never Really Liberal: Chris Licht Wants Him to ‘Hold People to Account’ (Video) The head of the network also said CNN is “shifting our approach to paid contributors,” after some paid contributors were notified about whether they were impacted by the network’s layoffs Wednesday. In a Wednesday morning memo Licht said full-time employees will be informed of their status on Thursday. He addressed departing colleagues in the Thursday memo, stating “I want to express my gratitude for your dedicated and tireless service and for your many contributions to CNN.”
2022-12-01T00:00:00
https://www.yahoo.com/entertainment/cnn-halts-live-programming-hln-001503109.html
[ { "date": "2022/12/01", "position": 92, "query": "AI layoffs" } ]
Labor
Labor
https://apnews.com
[]
Debate erupts over role job cuts played in weather forecasts ahead of ... Senate strikes AI regulatory ban from GOP bill after uproar from the states ...
The Associated Press is an independent global news organization dedicated to factual reporting. Founded in 1846, AP today remains the most trusted source of fast, accurate, unbiased news in all formats and the essential provider of the technology and services vital to the news business. More than half the world’s population sees AP journalism every day.
2022-12-01T00:00:00
https://apnews.com/hub/labor
[ { "date": "2022/12/01", "position": 98, "query": "AI layoffs" } ]
Layoffs and slow hiring have job seekers worried about AI. Here's ...
Layoffs and slow hiring have job seekers worried about AI. Here's what's happening.
https://www.nbcnews.com
[ "Https", "Media-Cldnry.S-Nbcnews.Com Image Upload Newscms", "Rob Wile", "Rob Wile Is A Pulitzer Prize-Winning Journalist Covering Breaking Business Stories For Nbcnews.Com." ]
A growing chorus of executives has put white collar workforces on notice: Their jobs are at risk of being wiped out by artificial intelligence.
A growing chorus of executives has put white collar workforces on notice: Their jobs are at risk of being wiped out by artificial intelligence. Yet above that din is a more complicated picture of how AI is currently affecting hiring. Direct evidence of an acceleration in human obsolescence remains scant so far. In a report this week, the job and hiring consultancy Challenger, Gray & Christmas said cuts spurred by President Donald Trump’s Department of Government Efficiency remained the leading cause of job losses — especially for government, nonprofit and other sectors supported by federal funds — followed by general economic and market conditions. Out of 286,679 planned layoffs so far this year, only 20,000 were linked to automation, the firm said — with just 75 explicitly tied to AI implementation. “Far less is happening than people imagine,” said Andrew Challenger, senior vice president at the consultancy, referring to the impact of AI on the broader workforce in the U.S. “There are roles that can be significantly changed by AI right now, but I’m not talking to too many HR leaders who say AI is replacing jobs.” That belies recent comments made by some of America’s most prominent executives about the impact that artificial intelligence is expected to have. Last month, Amazon CEO Andy Jassy warned that AI would “reduce our total corporate workforce as we get efficiency gains” over time. However, he did not lay out what that time frame might look like. He also said more people would likely be needed to do “other types of jobs,” ones that AI may help generate. And while The Wall Street Journal reported comments from Ford CEO Jim Farley this week that AI would replace “literally half of all white-collar workers in the U.S.,” a clip of Farley’s presentation offered more context. The automotive executive was speaking about beefing up America’s blue-collar workforce, and appeared to be repeating the warning about a white-collar wipeout issued by the CEO of the AI company Anthropic — a contention that is still being debated. (A representative for Ford did not respond to a request for comment.) Experts say the current era of AI is affecting the job market in more roundabout ways. Many firms are currently under tremendous pressure to cut costs given the generally uncertain economic environment spurred by the heavy cost of Trump’s tariff policy and worries about rising inflation. As a result, some companies are diverting spending that would otherwise be going to hiring more employees and shifting it toward AI software. “There’s basically a blank check to go out and buy these AI tools,” said Josh Bersin, CEO of The Josh Bersin Company workforce consultancy. “Then they go out and say, as far as head count: No more hiring. Just, ‘stop.’ So that immediately freezes the job market.” Among the most high-profile examples is Shopify, whose CEO told employees they must now prove why they “cannot get what they want done using AI” before asking for more employees and resources. “What would this area look like if autonomous AI agents were already part of the team?” Shopify CEO Tobi Lutke wrote in a memo sent to employees in March. “This question can lead to really fun discussions and projects.” The chief executive of language learning app Duolingo, Luis von Ahn, issued a similar edict in May, writing that the firm would gradually stop using contractors to do work that AI can handle and that a budget for new employees would only be given “if a team cannot automate more of their work.” Enough firms hedging in this way, alongside a wider economic slowdown, may indeed be suppressing overall hiring, especially in business and professional services. But those trends do not amount to large-scale replacement of existing workers by AI agents. Then there are the firms creating the AI tools themselves — the ones other businesses are ostensibly looking to purchase and deploy to automate their workforces. These AI developers, including Dell, Google parent Alphabet, Facebook parent Meta, Microsoft and Salesforce, have been shedding workers not tied to AI product development and shifting resources toward those who are. If AI is causing job losses, it’s not because it’s doing someone else’s job. It’s because budgets — and demands on the bottom line — are changing. The state of hiring at Microsoft is illustrative. Over the past several weeks, the tech giant — whose stock has surged 17% year to date thanks in part to the popularity of its Copilot AI tool — has announced job cuts affecting some 15,000 roles, or about 7% of its workforce. In this case, some human replacement does appear to be occurring: CEO Satya Nadella said recently that as much as 30% of the company’s code is now written by AI — something Bloomberg News confirmed in a report showing software engineering roles made up more than 40% of the roughly 2,000 positions cut in one of the recent layoff rounds. Yet other analysts indicated the cuts were also likely designed to offset the costs associated with Microsoft’s massive buildout of data centers designed to handle AI computer processing. “We believe that every year Microsoft invests at the current levels, it would need to reduce headcount by at least 10,000” in order to make up for its increased capital expenditures, said Gil Luria, a tech research analyst at D.A. Davidson financial group, in an interview with Reuters. In a note to clients, analysts with the consultancy Capital Economics said not all mentions of AI by businesses discussing their financial picture should be taken at face value. “For some firms, AI is a way to spin job losses driven by poor financial performance in a more positive light,” they wrote. AI is also affecting the hiring and recruiting process itself. A galaxy of startups now offers tools that can perform the job of entire HR departments, from scanning resumes to interviewing candidates. At IBM, “a couple hundred” HR workers have been recently replaced by AI agents, CEO Arvind Krishna told The Wall Street Journal in May. Yet with those efficiencies, the company was able to hire more programmers and salespeople, he said. “While we have done a huge amount of work inside IBM on leveraging AI and automation on certain enterprise workflows, our total employment has actually gone up, because what it does is it gives you more investment to put into other areas,” Krishna said. For anyone struggling to find new work, AI is not without blame. But experts say economic factors continue to vastly outweigh the threat from automation. “Our research has shown that AI will fundamentally change a whole lot of jobs, some by a lot,” said Svenja Gudell, chief economist at Indeed Hiring Lab. In the case of software developers especially, she said, roles are being completely transformed. “But does it still mean AI took that job? I don’t think so,” she said. “There’s not evidence that it’s fully replacing whole workers, or that the current slowdown can be attributed to it.”
2025-07-05T00:00:00
2025/07/05
https://www.nbcnews.com/business/business-news/is-ai-taking-jobs-which-industries-at-risk-what-to-know-rcna215579
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Will A.I. Replace New Hires or Middle Managers?
Which Workers Will A.I. Hurt Most: The Young or the Experienced?
https://www.nytimes.com
[ "Noam Scheiber" ]
Amid layoffs at Microsoft and other large tech companies, experts are debating whose jobs are most likely to be spared.
Over the same period, employment in these industries has increased for workers with two or more years of job tenure, according to Ruyu Chen, a Stanford researcher who analyzed the data. Other studies point in a similar direction, if in a roundabout way. In early 2023, Italy temporarily banned ChatGPT, which software developers there relied on to help them code. A team of researchers at the University of California, Irvine, and Chapman University compared the change in the productivity of Italian coders with the productivity of coders in France and Portugal, which did not ban the software, to isolate the impact of ChatGPT. While the study did not look at job loss, it did find that the A.I. tool had transformed the jobs of midlevel workers in more favorable ways than the jobs of entry-level workers. According to the researchers, the junior coders used A.I. to complete their tasks somewhat faster; the experienced coders often used it to benefit their teams more broadly. For example, the A.I. helped midlevel coders review the work of other coders and suggest improvements, and to contribute to projects in languages they didn’t know. “When people are really good at things, what they end up doing is helping other people as opposed to working on their own projects,” said Sarah Bana, one of the paper’s authors, adding that the A.I. essentially reinforced this tendency. Dr. Bana said the paper’s result suggested that A.I. would prompt companies to hire fewer junior coders (because fewer would be needed to complete entry-level tasks) but more midlevel coders (because A.I. amplified their value to their whole team). On the other hand, Danielle Li, an economist at M.I.T. who studies the use of A.I. in the workplace, said there were scenarios in which A.I. could undermine higher-skilled workers more than entry-level workers. The reason is that it can, in effect, untether valuable skills from the humans who have traditionally possessed them. For instance, you may no longer have to be an engineer to code, or a lawyer to write a legal brief.
2025-07-07T00:00:00
2025/07/07
https://www.nytimes.com/2025/07/07/business/ai-job-cuts.html
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intelligence workers" }, { "date": "2024/06/01", "position": 3, "query": "AI job losses" }, { "date": "2024/06/01", "position": 1, "query": "AI replacing workers" }, { "date": "2024/06/01", "position": 2, "query": "AI workers" }, { "date": "2024/06/01", "position": 2, "query": "artificial intelligence layoffs" }, { "date": "2024/07/01", "position": 61, "query": "AI job losses" }, { "date": "2024/07/01", "position": 1, "query": "AI replacing workers" }, { "date": "2024/07/01", "position": 1, "query": "artificial intelligence workers" }, { "date": "2024/07/01", "position": 43, "query": "generative AI jobs" }, { "date": "2024/08/01", "position": 63, "query": "AI job losses" }, { "date": "2024/08/01", "position": 91, "query": "AI unemployment rate" }, { "date": "2024/08/01", "position": 2, "query": "artificial intelligence layoffs" }, { "date": "2024/08/01", "position": 56, "query": "generative AI jobs" }, { "date": "2024/09/01", "position": 80, "query": "AI impact jobs" }, { "date": "2024/09/01", "position": 56, "query": "generative AI jobs" }, { "date": "2024/10/01", "position": 79, "query": "AI impact jobs" }, { "date": "2024/10/01", "position": 1, "query": "AI replacing workers" }, { "date": "2024/11/01", "position": 78, "query": "AI impact jobs" }, { "date": "2024/11/01", "position": 1, "query": "AI replacing workers" }, { "date": "2024/11/01", "position": 2, "query": "AI workers" }, { "date": "2024/11/01", "position": 40, "query": "generative AI jobs" }, { "date": "2024/12/01", "position": 1, "query": "AI replacing workers" }, { "date": "2024/12/01", "position": 2, "query": "AI workers" }, { "date": "2024/12/01", "position": 1, "query": "artificial intelligence workers" }, { "date": "2025/01/01", "position": 3, "query": "AI job losses" }, { "date": "2025/01/01", "position": 1, "query": "AI replacing workers" }, { "date": "2025/01/01", "position": 59, "query": "generative AI jobs" }, { "date": "2025/02/01", "position": 2, "query": "AI replacing workers" }, { "date": "2025/02/01", "position": 3, "query": "AI workers" }, { "date": "2025/02/01", "position": 2, "query": "artificial intelligence layoffs" }, { "date": "2025/03/01", "position": 2, "query": "artificial intelligence layoffs" }, { "date": "2025/04/01", "position": 2, "query": "AI replacing workers" }, { "date": "2025/04/01", "position": 70, "query": "AI unemployment rate" }, { "date": "2025/04/01", "position": 1, "query": "artificial intelligence layoffs" }, { "date": "2025/05/01", "position": 3, "query": "AI replacing workers" }, { "date": "2025/05/01", "position": 3, "query": "AI workers" }, { "date": "2025/05/01", "position": 3, "query": "artificial intelligence workers" }, { "date": "2025/06/01", "position": 53, "query": "AI job losses" }, { "date": "2025/06/01", "position": 2, "query": "AI replacing workers" }, { "date": "2025/06/01", "position": 2, "query": "artificial intelligence layoffs" }, { "date": "2025/06/01", "position": 3, "query": "artificial intelligence workers" } ]
Career Opportunities: Work with Us - C3 AI
Career Opportunities: Work with Us
https://c3.ai
[]
C3 AI provides tremendous career opportunities to professionals who are willing to work hard, on meaningful challenges alongside a talented team.
Paid Parental Time Off For US employees, mothers are eligible for up to a total of 10 to 12 weeks of paid parental time off with your newborn. All parents, including those adopting children, are eligible to take up to a total of 4 weeks of paid parental time off. Advanced Degrees Lifelong learning is a part of C3 AI. That’s why we will cover the total cost for employees to earn a master’s degree in computer science online. Those who complete the degree get three more big perks—a $25,000 cash bonus, a guaranteed 15% raise and a stock grant. Continuous Education C3 AI holds monthly employee training sessions as well as weekly lunch-and-learns. C3 AI also encourages further education by offering bonuses for the successful completion of select online courses. Relax and recharge In the United States, C3 AI offers 15 days of paid time off every year. As your tenure with the company grows so does your paid time off! C3 AI also offers 10 paid public holidays around which you can build your vacation leave. Health coverage C3 AI offers competitive coverage. Our program includes medical, dental, and vision. 401K C3 AI offers fund options via Charles Schwab for retirement savings. Equity Restricted stock units are granted to all full-time C3 AI employees. Free gym membership To help keep you at the top of your game, C3 AI offers employees a free gym membership at our state-of-the-art fitness center in Redwood City, CA. Catered lunches daily C3 AI provides a fully stocked snack area and beverage refrigerator that contains everything from energy drinks to sodas and iced tea. Every day C3 AI provides a catered, gourmet lunch so that the team can relax together and share ideas. Commuter check program C3 AI offers tax saving commuter benefits program. Travel assistance Employees are provided global health insurance while traveling for business Ping-pong and pool tables C3 AI has been known to host ping-pong and pool tournaments, allowing you to step away from the monitor. This is the perfect opportunity to enjoy coworkers while hitting a white ball at them. Friday happy hour Relax and unwind at the end of the week at C3’s weekly Friday Happy Hour. Enjoy good food, good drinks and great company at our office. Flexible spending accounts C3 AI offers both Health Care and Dependent Care Flexible Spending Accounts. Both accounts enable you to pay for essential health and wellness before you pay taxes on it. Life insurance C3 AI offers short term / long term disability, life insurance and AD&D insurance. Additional leave benefits C3 AI offers paid time off for bereavement and jury leave.
2022-12-01T00:00:00
https://c3.ai/careers/
[ { "date": "2022/12/01", "position": 13, "query": "AI employment" }, { "date": "2023/01/01", "position": 19, "query": "AI employment" }, { "date": "2023/02/01", "position": 12, "query": "AI employment" }, { "date": "2023/04/01", "position": 11, "query": "AI employment" }, { "date": "2023/04/01", "position": 22, "query": "generative AI jobs" }, { "date": "2023/05/01", "position": 11, "query": "AI employment" }, { "date": "2023/05/01", "position": 24, "query": "generative AI jobs" }, { "date": "2023/06/01", "position": 11, "query": "AI employment" }, { "date": "2023/06/01", "position": 23, "query": "generative AI jobs" }, { "date": "2023/07/01", "position": 22, "query": "generative AI jobs" }, { "date": "2023/08/01", "position": 12, "query": "AI employment" }, { "date": "2023/09/01", "position": 21, "query": "generative AI jobs" }, { "date": "2023/10/01", "position": 23, "query": "generative AI jobs" }, { "date": "2023/11/01", "position": 11, "query": "AI employment" }, { "date": "2023/11/01", "position": 22, "query": "generative AI jobs" }, { "date": "2023/12/01", "position": 11, "query": "AI employment" }, { "date": "2023/12/01", "position": 22, "query": "generative AI jobs" }, { "date": "2024/01/01", "position": 11, "query": "AI employment" }, { "date": "2024/01/01", "position": 25, "query": "generative AI jobs" }, { "date": "2024/02/01", "position": 6, "query": "AI employment" }, { "date": "2024/02/01", "position": 24, "query": "generative AI jobs" }, { "date": "2024/03/01", "position": 23, "query": "generative AI jobs" }, { "date": "2024/06/01", "position": 11, "query": "AI employment" }, { "date": "2024/07/01", "position": 12, "query": "AI employment" }, { "date": "2024/07/01", "position": 20, "query": "generative AI jobs" }, { "date": "2024/08/01", "position": 26, "query": "generative AI jobs" }, { "date": "2024/09/01", "position": 23, "query": "generative AI jobs" }, { "date": "2024/11/01", "position": 9, "query": "AI employment" }, { "date": "2024/11/01", "position": 23, "query": "generative AI jobs" }, { "date": "2025/01/01", "position": 9, "query": "AI employment" }, { "date": "2025/01/01", "position": 24, "query": "generative AI jobs" }, { "date": "2025/02/01", "position": 15, "query": "AI employment" }, { "date": "2025/03/01", "position": 19, "query": "AI employment" }, { "date": "2025/05/01", "position": 15, "query": "AI employment" }, { "date": "2025/06/01", "position": 18, "query": "AI employment" } ]
Careers - Figure AI
Careers
https://www.figure.ai
[]
We're hiring candidates who are hungry to make their impact across AI, engineering and design at our headquarters in San Jose, CA.
Have another role in mind? Let us know what you could bring to the team. Figure is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.
2022-12-01T00:00:00
https://www.figure.ai/careers
[ { "date": "2022/12/01", "position": 22, "query": "AI employment" }, { "date": "2023/01/01", "position": 41, "query": "AI hiring" }, { "date": "2023/01/01", "position": 31, "query": "AI employment" }, { "date": "2023/02/01", "position": 43, "query": "AI hiring" }, { "date": "2023/02/01", "position": 40, "query": "AI employment" }, { "date": "2023/03/02", "position": 52, "query": "artificial intelligence employment" }, { "date": "2023/03/01", "position": 24, "query": "AI hiring" }, { "date": "2023/03/02", "position": 3, "query": "AI employment" }, { "date": "2023/03/02", "position": 6, "query": "artificial intelligence hiring" }, { "date": "2023/04/01", "position": 45, "query": "AI employment" }, { "date": "2023/05/01", "position": 40, "query": "AI employment" }, { "date": "2023/06/01", "position": 44, "query": "AI employment" }, { "date": "2023/08/01", "position": 43, "query": "AI employment" }, { "date": "2023/08/01", "position": 47, "query": "AI hiring" }, { "date": "2023/09/01", "position": 48, "query": "AI hiring" }, { "date": "2023/11/01", "position": 30, "query": "AI employment" }, { "date": "2023/12/01", "position": 44, "query": "AI employment" }, { "date": "2023/12/01", "position": 48, "query": "AI hiring" }, { "date": "2024/01/01", "position": 46, "query": "AI employment" }, { "date": "2024/01/01", "position": 37, "query": "AI hiring" }, { "date": "2024/02/01", "position": 50, "query": "AI employment" }, { "date": "2024/06/01", "position": 44, "query": "AI employment" }, { "date": "2024/06/01", "position": 51, "query": "AI hiring" }, { "date": "2024/07/01", "position": 33, "query": "AI employment" }, { "date": "2024/10/01", "position": 44, "query": "AI hiring" }, { "date": "2024/11/01", "position": 43, "query": "AI employment" }, { "date": "2025/01/01", "position": 45, "query": "AI employment" }, { "date": "2025/01/01", "position": 45, "query": "AI hiring" }, { "date": "2025/02/01", "position": 28, "query": "AI employment" }, { "date": "2025/02/01", "position": 28, "query": "AI hiring" }, { "date": "2025/03/01", "position": 39, "query": "AI employment" }, { "date": "2025/04/01", "position": 19, "query": "AI hiring" }, { "date": "2025/05/01", "position": 40, "query": "AI employment" }, { "date": "2025/06/01", "position": 40, "query": "AI employment" }, { "date": "2025/06/01", "position": 23, "query": "AI hiring" } ]
Official AI Job Board - Find Artificial Intelligence Jobs Free
Find Artificial Intelligence Jobs Free
https://www.aijobs.com
[]
The official free AI job board marketplace to discover the best career opportunities working in Artificial Intelligence, Machine Learning, Data Science, NLP, ...
The Official AI Job Board Welcome to the official free AI job board marketplace to discover the best career opportunities working in Artificial Intelligence, Machine Learning, Data Science, NLP, AI Research, Robotics, Computer Vision, and much more. Join for free!
2022-12-01T00:00:00
https://www.aijobs.com/
[ { "date": "2022/12/01", "position": 26, "query": "AI employment" }, { "date": "2023/01/01", "position": 56, "query": "AI employment" }, { "date": "2023/02/01", "position": 23, "query": "AI employment" }, { "date": "2023/04/01", "position": 24, "query": "AI employment" }, { "date": "2023/05/01", "position": 33, "query": "AI employment" }, { "date": "2023/06/01", "position": 25, "query": "AI employment" }, { "date": "2023/08/01", "position": 26, "query": "AI employment" }, { "date": "2023/11/01", "position": 25, "query": "AI employment" }, { "date": "2023/12/01", "position": 25, "query": "AI employment" }, { "date": "2024/01/01", "position": 26, "query": "AI employment" }, { "date": "2024/06/01", "position": 25, "query": "AI employment" }, { "date": "2024/07/01", "position": 24, "query": "AI employment" }, { "date": "2024/11/01", "position": 30, "query": "AI employment" }, { "date": "2025/01/01", "position": 32, "query": "AI employment" } ]
Jobright: Your AI Job Search Copilot
Jobright: Your AI Job Search Copilot
https://jobright.ai
[]
Discover your dream job with Jobright, your AI job search copilot. Get tailored resumes, social connections, and autofill jobs applilcations for your fit.
Thank you for your praise and suggestions. With your support, we can go further. We hope to accompany you throughout your job search journey. I am able to find more relevant jobs faster, since using Jobright I have tripled my interview rate. I am truly impressed. Fred H. / Senior Software Engineer Thanks to this platform I’ve landed a few interviews and accepted an offer within 1 week of interviewing!! Tracy C. / Sr. Digital Marketing Manager You must check out Jobright. It has been saving me hours in my job search! I’m blown away at how easy it is to use!! Tyler S. / Instructional Designer I’ve enjoyed seeing so many matching jobs. This has completely revamped my job search process. Excited to keep exploring! Chelsea L. / Senior Recruiter It’s a 10/10!! Especially the resume editor which helps me very easily write the content to match the job description. The AI guidance and support has been game changing. Loving it so far! Brandi G. / Software Engineer Not only does jobright show you the most relevant jobs it ALSO helps you network and get potential referrals! The matching system uses my experience, skills, and so much more to find the best fit. Definitely recommend! Gabriella B. / LinkedIn Strategist
2022-12-01T00:00:00
https://jobright.ai/
[ { "date": "2022/12/01", "position": 31, "query": "AI employment" }, { "date": "2023/01/01", "position": 35, "query": "AI employment" }, { "date": "2023/02/01", "position": 32, "query": "AI employment" }, { "date": "2023/04/01", "position": 36, "query": "AI employment" }, { "date": "2023/05/01", "position": 32, "query": "AI employment" }, { "date": "2023/06/01", "position": 32, "query": "AI employment" }, { "date": "2023/08/01", "position": 33, "query": "AI employment" }, { "date": "2024/06/12", "position": 72, "query": "artificial intelligence hiring" }, { "date": "2025/02/01", "position": 25, "query": "AI employment" }, { "date": "2025/03/01", "position": 25, "query": "AI employment" }, { "date": "2025/05/01", "position": 21, "query": "AI employment" }, { "date": "2025/06/01", "position": 24, "query": "AI employment" } ]
AI - Technology Teams | Meta Careers
Technology Teams
https://www.metacareers.com
[]
AI to Wearables, Research to Infrastructure — find the team that speaks to you. Whether you're a research scientist, visual architect, software engineer or ...
Equal Employment Opportunity Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here. Meta is committed to providing reasonable support (called accommodations) in our recruiting processes for candidates with disabilities, long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support. If you need assistance or an accommodation due to a disability, fill out the Accommodations request form .
2022-12-01T00:00:00
https://www.metacareers.com/teams/technology?tab=AI
[ { "date": "2022/12/01", "position": 36, "query": "AI employment" }, { "date": "2023/01/01", "position": 36, "query": "AI employment" }, { "date": "2023/02/01", "position": 35, "query": "AI employment" }, { "date": "2023/04/01", "position": 38, "query": "AI employment" }, { "date": "2023/05/01", "position": 36, "query": "AI employment" }, { "date": "2023/06/01", "position": 38, "query": "AI employment" }, { "date": "2023/08/01", "position": 34, "query": "AI employment" }, { "date": "2023/10/26", "position": 20, "query": "AI employment" }, { "date": "2023/10/26", "position": 38, "query": "AI hiring" }, { "date": "2023/10/26", "position": 86, "query": "artificial intelligence wages" }, { "date": "2023/10/26", "position": 48, "query": "artificial intelligence workers" }, { "date": "2023/10/01", "position": 14, "query": "generative AI jobs" }, { "date": "2023/11/01", "position": 37, "query": "AI employment" }, { "date": "2023/12/01", "position": 35, "query": "AI employment" }, { "date": "2024/01/01", "position": 39, "query": "AI employment" }, { "date": "2024/02/01", "position": 40, "query": "AI employment" }, { "date": "2024/06/01", "position": 33, "query": "AI employment" }, { "date": "2024/07/01", "position": 34, "query": "AI employment" }, { "date": "2024/09/01", "position": 12, "query": "generative AI jobs" }, { "date": "2024/11/01", "position": 35, "query": "AI employment" }, { "date": "2025/01/01", "position": 34, "query": "AI employment" }, { "date": "2025/02/01", "position": 33, "query": "AI employment" }, { "date": "2025/03/01", "position": 35, "query": "AI employment" }, { "date": "2025/05/01", "position": 44, "query": "AI employment" }, { "date": "2025/06/01", "position": 41, "query": "AI employment" } ]
CEOs Start Saying the Quiet Part Out Loud: AI Will Wipe Out Jobs
The heart of the internet
https://www.reddit.com
[]
If they could do it, they would have done it already. Current AI is a scam, CEO's are using it as an excuse to layoff expensive employees in the ...
Subreddit dedicated to the news and discussions about the creation and use of technology and its surrounding issues. Members Online
2022-12-01T00:00:00
https://www.reddit.com/r/technology/comments/1lsvg5y/ceos_start_saying_the_quiet_part_out_loud_ai_will/
[ { "date": "2022/12/01", "position": 37, "query": "AI employment" }, { "date": "2023/01/01", "position": 42, "query": "AI employment" }, { "date": "2023/02/01", "position": 34, "query": "AI employment" }, { "date": "2023/04/01", "position": 33, "query": "AI employment" }, { "date": "2023/05/01", "position": 30, "query": "AI employment" }, { "date": "2023/06/01", "position": 35, "query": "AI employment" }, { "date": "2023/08/01", "position": 29, "query": "AI employment" }, { "date": "2023/11/01", "position": 29, "query": "AI employment" }, { "date": "2023/12/01", "position": 33, "query": "AI employment" }, { "date": "2024/01/01", "position": 34, "query": "AI employment" }, { "date": "2024/02/01", "position": 29, "query": "AI employment" }, { "date": "2024/06/01", "position": 35, "query": "AI employment" }, { "date": "2024/07/01", "position": 32, "query": "AI employment" }, { "date": "2024/11/01", "position": 32, "query": "AI employment" } ]
Careers | Scale AI
Scale AI
https://scale.com
[]
At Scale, we believe your talent and achievements deserve to be met with a supportive community and flexible environment.
The age of AI is here. Generative AI has the potential to unseat incumbents, catapult new leaders, or solidify existing moats. Every industry, from the private sector to public sector is rethinking their strategies to incorporate AI. Despite this explosion in interest, there is no blueprint for organizations to go from inception to deployment for their AI initiatives.
2022-12-01T00:00:00
https://scale.com/careers
[ { "date": "2022/12/01", "position": 39, "query": "AI employment" }, { "date": "2023/01/01", "position": 32, "query": "AI employment" }, { "date": "2023/02/01", "position": 10, "query": "generative AI jobs" }, { "date": "2023/02/01", "position": 46, "query": "AI employment" }, { "date": "2023/04/01", "position": 9, "query": "generative AI jobs" }, { "date": "2023/05/01", "position": 10, "query": "generative AI jobs" }, { "date": "2023/06/01", "position": 9, "query": "generative AI jobs" }, { "date": "2023/07/01", "position": 8, "query": "generative AI jobs" }, { "date": "2023/09/01", "position": 8, "query": "generative AI jobs" }, { "date": "2023/10/01", "position": 8, "query": "generative AI jobs" }, { "date": "2023/11/01", "position": 10, "query": "generative AI jobs" }, { "date": "2023/12/01", "position": 7, "query": "generative AI jobs" }, { "date": "2024/01/01", "position": 11, "query": "generative AI jobs" }, { "date": "2024/02/01", "position": 9, "query": "generative AI jobs" }, { "date": "2024/03/01", "position": 11, "query": "generative AI jobs" }, { "date": "2024/04/01", "position": 9, "query": "generative AI jobs" }, { "date": "2024/07/01", "position": 11, "query": "generative AI jobs" }, { "date": "2024/08/01", "position": 9, "query": "generative AI jobs" }, { "date": "2024/09/01", "position": 9, "query": "generative AI jobs" }, { "date": "2024/11/01", "position": 9, "query": "generative AI jobs" }, { "date": "2025/01/01", "position": 10, "query": "generative AI jobs" }, { "date": "2025/02/01", "position": 32, "query": "AI employment" }, { "date": "2025/02/01", "position": 8, "query": "generative AI jobs" }, { "date": "2025/03/01", "position": 44, "query": "AI employment" }, { "date": "2025/03/01", "position": 7, "query": "generative AI jobs" }, { "date": "2025/04/01", "position": 7, "query": "generative AI jobs" }, { "date": "2025/05/01", "position": 43, "query": "AI employment" }, { "date": "2025/06/01", "position": 46, "query": "AI employment" }, { "date": "2025/06/01", "position": 8, "query": "generative AI jobs" } ]
Jobs and Talents in AI, ML, Data Science and Big Data | aijobs.net
Jobs and Talents in AI, ML, Data Science and Big Data
https://aijobs.net
[]
Explore AI, ML, Data Science jobs globally. Search for vacancies in metropolitan areas with the highest demand for AI, ML, Data Science professionals worldwide.
Looking for more? Try foo🦍 - the career platform for coders, builders, hackers and makers :) Got questions or feedback? Drop us a message at hey `at` aijobs `dot` net.
2022-12-01T00:00:00
https://aijobs.net/
[ { "date": "2022/12/01", "position": 41, "query": "AI employment" }, { "date": "2023/01/01", "position": 45, "query": "AI employment" }, { "date": "2023/02/01", "position": 36, "query": "AI employment" }, { "date": "2023/04/01", "position": 39, "query": "AI employment" }, { "date": "2023/05/01", "position": 37, "query": "AI employment" }, { "date": "2023/06/01", "position": 34, "query": "AI employment" }, { "date": "2023/08/01", "position": 30, "query": "AI employment" }, { "date": "2023/11/01", "position": 36, "query": "AI employment" }, { "date": "2023/12/01", "position": 38, "query": "AI employment" }, { "date": "2024/01/01", "position": 36, "query": "AI employment" }, { "date": "2024/02/01", "position": 43, "query": "AI employment" }, { "date": "2024/06/01", "position": 42, "query": "AI employment" }, { "date": "2024/07/01", "position": 37, "query": "AI employment" }, { "date": "2024/11/01", "position": 40, "query": "AI employment" }, { "date": "2025/01/01", "position": 41, "query": "AI employment" }, { "date": "2025/02/01", "position": 34, "query": "AI employment" }, { "date": "2025/03/01", "position": 33, "query": "AI employment" }, { "date": "2025/05/01", "position": 36, "query": "AI employment" }, { "date": "2025/06/01", "position": 34, "query": "AI employment" } ]
AI Jobs Growth - All US
AI Jobs Growth
https://www.aimaps.ai
[]
New AI job listings are up 42% compared with a December 2022 low point, according to University of Maryland researchers.
“Amazon had more than 7,500 AI job postings in 2021, more than 6,000 in 2022 and more than 1,000 in 2023, according to the analysis from the University of Maryland. In the first six months of 2024, it posted more than 2,600 roles….Meta, the parent company of Facebook and Instagram, has had the third-highest number of AI job postings in King County — behind Amazon and Microsoft — for three of the last four years. Google briefly surpassed it in 2023.”
2022-12-01T00:00:00
https://www.aimaps.ai/
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Why AI Harm To Jobs and Humanity are Vastly Over-Hyped
Why AI Harm To Jobs and Humanity are Vastly Over-Hyped
https://joshbersin.com
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Despite talk of Superintelligence, AI is not about to destroy our jobs or our lives. Here are four big reasons not to worry.
I’m continuously surprised by the hyperbolic articles and comments about AI ruining the job market, the web, or our lives. Yuval Noah Harari believes this is an existential change to humanity. Mark Benioff claims that 30-50% of Salesforce ops is now done by AI. And media sites like The Verge (Nilay Patel) worry that all their Google web traffic will go away. While nobody can predict the future, I do talk with hundreds of companies each month and probably meet with 5 or more software vendors each week, so I have a good sense of what’s going on. And as I describe in “The Rise of The Superworker,” many of these fears are unfounded. By contrast, I’m firmly convinced that AI tools and platforms are going to unleash personal creativity, business growth, and innovation. And this will create many jobs, lift wages, and improve our working lives (and businesses). Here’s my argument, largely based on our own experiences with Galileo (our AI platform) and many corporate and vendor clients. First, the widespread “wipeout” of white collar jobs is simply not yet happening. Yes, there is some softness in hiring, but this is largely because IT budgets are up 62% and CEOs are forcing business leaders to “adopt” AI. This push-effect has slowed hiring and almost all the companies I talk with are trying to figure out how to reorganize jobs and roles to improve automation for white-collar jobs. I talk with senior HR leaders every day and there is a unanimous story: the CEO and CFO have mandated a shift to AI so “stop hiring workers and get going implementing AI.” So hiring budgets are frozen. While the push makes sense, much of this has not worked out yet, simply because the off the shelf tools (MS Copilot, SAP Joule, ChatGPT) are not yet built out into complete applications. So at this point it’s not completely clear what jobs to change, what routine work to eliminate, and what AI to buy (or build). (Read my article about Job Redesign for more, or listen to my podcast about WPP’s massive organizational redesign.) If you look at our four-stage AI transformation model, my guess is that 60% of companies are at stage 1, 30% at stage 2, and 10% or fewer at stage 3 (within different business functions). I know, for example, that Chipotle is using Paradox to implement a Stage 3 approach to recruiting, (as is H&M with Maki People), and our own HR Academy is now at Stage 3 using Galileo Learn. But generally speaking, it’s not clear that sales automation, lead gen (I’m getting so many junk emails from “Agents” now it’s becoming a massive turnoff from those providers), contract management, marketing (our Hubspot system is not as “intelligent” as we’d like yet), procurement, A/R, are here yet. It’s coming, but not at all mature. I’d love to see Marc Benioff in his next financial analyst call, actually explain how much money he’s changed an list the “50% of jobs” he’s automated. I doubt he will. (Salesforce’s organic revenue growth is around 8% and its employee count, according to LinkedIn, is growing at 4%. So the company is becoming very slightly more productive but nothing like Benioff seems to claim.) So while all these promises are coming, the actual details behind all these business processes are quite complex (and personal to each company), so there is a 1-2 year “development cycle” yet to happen. Last week, for example, I was in the Middle East and met with many companies including one of the largest airlines. The HR team there was just starting a major re-engineering look at their HR processes and while the vision was becoming clear, we realized that most of the “products” they need are not here yet. They’re doing the redesign, and now looking for AI solutions. This, by the way, is why I think most of the corporate AI re-engineering will be internally built, in partnership with vendors. We’re done with the “buy Workday and turn it on” approach to business software and automation – these AI agents will be infinitely configurable so companies have to have a sense of what they want to do. It’s coming for sure, but not at all here yet. Second, for each “agent” we use, many new jobs are created. We’ve now seen more than 4,000 people buy and “turn on” our own Galileo agent, for example. Every single one of these users has come back with new “work” to do (finding data, cleaning up processes, etc.) because routine, mind-numbing work went away. This is the “Superworker” effect. It’s kind of like what happens when you buy a leaf-blower: the leaves don’t “go away” and you don’t throw away your broom. It just lets you blow the leaves 10X faster, but then you have to bag them and put them on the street for recycling. Now recyclers get more leaves, you get to trim the hedges (another job for a robot), and the leaf-blower company makes more money. In other words, automation of one task leads all of us to do higher level things, and this is going to continue forever. In other words, we become “Superworkers,” upgrading our value to our jobs and our companies. And “managing” these tools also takes time (learning prompts, finding quality data, iterating, training, and securing systems). This week I saw another new AI tool that does FP&A (finance, planning, and administration). This is something every company needs, yet the old tools are so manual they’re almost a nightmare to use. This new system (I’ll tell you more when it’s launched) looks at your financials, CRM, and HRMS and “finds and shows you” profit gaps, slowdowns, and budget over-runs automatically. This takes me and our CFO hours to do by hand. This Superworker effect is taking place now: the US unemployment rate remains very low (4.2%) and as I discussed in my recent article about entry level work, the “job market” is dealing with a few hiccups but there will be white collar jobs for decades to come. We’re just in a transition period. I’m guessing that when the “web” started (around 1998) people expected “books” to go away. (And retail stores.) Well what happened was precisely what happens here: book writers and retailers “evolved” to use, leverage, and exploit the web. Now, 27 years later, we use the “web” for all sorts of advanced hybrid solutions (Substack itself for example, and hybrid e-commerce and mobile ordering), which just forced book writers and retailers to adapt. (And to my knowledge book publishing is flourishing.) Writing a book is still a worthwhile endeavor, but many “writers” would now prefer to build Substacks and generate an audience without being held hostage to Amazon. Another Superworker effect. (Once you think about it you’ll see it everywhere.) This “creative re-engineering” of our work, jobs, and lives will continue at an accelerating rate. I tell our clients that “you’re all developers now!” Just use the english language (or your own) and learn how to “program and automate” your own work, live, and business. Third, AI is not quite as “smart” as AI engineers believe. Despite the fascination with AI SuperIntelligence and other GAI models, the human genome is 1000X more sophisticated than the advanced mathematics inherent to AI. Our genome is the epigenetic result of millions of years of evolution, and this is why human beings are so empathetic, creative, passionate, and often unpredictable. (70 Trillion combinations of proteins make up our DNA, and each cell type is different. That DNA encodes millions of years of learning, evolution, environment, and experiences. And some scientists think it’s infinite. Take THAT Nvidia!) These “human” skills of perception, empathy, creativity, ambition, passion, grit, and innovation are nowhere to be found in AI. AI is a very powerful “analytic” engine and yes, it will learn more and more from our experiences. Yes, Meta just announced its “Superintelligence Lab,” but let’s be honest. This is all about selling advertisements (and maybe creating romance bots). Is that going to change our businesses? Other than pinpointing even more advertising (now you could presumably by an ad for “people who are anxious about dating older women”), I doubt it. In another vein, I am excited about “physical AI”, the decoding of physics, light, momentum, and other physical aspects of life, desperately needed for autonomous vehicles and humanoid robots (and war). I saw a demo in the Middle East of a network of Boston Dynamics crawlers (they’re definitely creepy) all programmed to monitor and support safety in oil refineries. (Just today at the gym I was talking with my trainer about the robots that could clean up the 100 pound weights people keep leaving on the floor.) I worked in a refinery early in my career and one year we had a sulphur dioxide leak which killed a refinery operator. That horrible experience alone would easily justify a multi-million dollar robot monitoring system, which I’d imagine is now rolling out in many plants, chemical facilities, and energy companies. (I also visited several nuclear plants early in my career and I was always creeped out when I was told “don’t get any closer to that valve because it’s highly radioactive” when you can’t see or feel anything!) So there are thousands of amazing use-cases for AI. But does that mean the autonomous car or refinery robot is “feeling” or “understanding” the nuances of the road, plant, or weather? Sure over time all those signals will be coded, but we humans are so much more adaptable and we will always “rise above” these machines. And that leads me to my fourth point. Fourth, it’s humans who create new ideas, businesses, and industries. Remember also that it’s people who “think up” the new business models, innovations, products, and services that drive value. If AI were so “smart,” why wouldn’t it start it’s own company? 🙂 Every breakthrough product, science, company, or idea comes from a human being. We humans are wired as “learning animals” (starting from birth), and our complex instincts of survival, fear, learning, ego, empathy, patience, forgiveness, and triumph are what makes us all entrepreneurs, creators, caretakers, or even politicians. This complex tapestry of “intelligences” is what builds companies like Apple, Microsoft, Nike, and Disney. Behind each of these amazing businesses was a person (or a few people) who “thought up” something new that was missing and badly needed in the world. In the case of AI, we’re all going to have automation agents. It’s tantalizingly easy to buy a bot and use it or “turn it on” for routine work. (We automated our editing and transcription process in a few days.) But how we are pivoting our business toward “intelligent HR and talent solutions” with our Galileo platform was a human idea, incubated in my head, and curated through the work of our management team and our partners. And this “human intelligence” thrives under stress. Look at the creativity of the Ukranian military. Look at how quickly we adapted to the pandemic. Look at how people with chronic disease and disabilities learn to adapt. There’s something mystical in our human intelligence, and ideas like “Morality” are fully human. Lord Jonathan Sacks, the chief Rabbi of the UK, wrote about it eloquently in his wonderful and famous book. I call this “the Unquenchable Power of the Human Spirit,” and I see it again and again in our clients. When times are tough or uncertain (witness the pandemic), human beings adapt, learn, and pull together in teams in subtle human ways. I have no evidence that AI has this type of historic intelligence. I was talking with the CTO of Sana, our partners in Galileo, about this, and he agreed with me that AI does not understand “history” and the cause and effects of time-based learning. I’ll write more about this as I talk with more scientists, but I still believe that we, the humans, are far more adaptable and “learning agile” than these data systems. Bottom Line: Our Jobs and Lives are Safe The bottom line for me is this: AI is a tool. We can make it or teach it to do whatever we want. If we let it get away from is it may hurt us (as will a lawnmower or a power saw). It’s up to us, as high-level thinking humans, to simply learn about this tool, understand how to use it, and apply it to our jobs, companies, and lives. Life will go on, economies will continue to be driven by emotion, and our businesses will continue to be fueled by human ideas, emotion, grit, and hard work. Additional Information Get Galileo, The AI Agent Designed Exclusively for HR and Leadership
2025-07-01T00:00:00
2025/07/01
https://joshbersin.com/2025/07/why-ai-harm-to-jobs-and-humanity-are-vastly-over-hyped/
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16 Artificial Intelligence Career Paths - California Miramar University
16 Artificial Intelligence Career Paths
https://www.calmu.edu
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Curious about artificial intelligence career paths and the essential skills you need to thrive in the industry? ✓ Discover 16 AI-related jobs today here.
Artificial intelligence (AI) is transforming industries at an unprecedented pace. In fact, 72% of organizations use AI technology to improve at least one business function. From healthcare and finance to logistics and beyond, AI-driven solutions allow businesses to achieve next-level efficiency and laser-focused decision-making. As the demand for AI professionals continues to grow, understanding the potential career paths in this growing field is critical for students looking for rewarding and in-demand careers. This blog dives into 16 artificial intelligence career paths and highlights the essential skills and qualifications required to succeed in them. Understanding Artificial Intelligence Artificial Intelligence is the branch of computer science dedicated to creating systems that simulate human intelligence. These AI applications are designed to perform tasks such as learning, reasoning, problem-solving, and decision-making. AI's core “ingredients” include: Machine Learning (ML): Algorithms that enable machines to learn from data Algorithms that enable machines to learn from data Deep Learning (DL): Advanced neural networks that process complex patterns in data Advanced neural networks that process complex patterns in data Natural Language Processing (NLP): Tools that allow machines to understand and interact with human language Tools that allow machines to understand and interact with human language Computer Vision (CV): Systems that interpret visual data like images and videos AI has changed dramatically since its start in the mid-20th century. Initially focused on theoretical possibilities, AI today powers applications like autonomous vehicles, voice assistants (e.g., Siri, Alexa), and predictive analytics tools. Industries like healthcare, finance, and logistics are using AI to improve outcomes and free human employees from monotonous tasks so they can focus on creative and high-value work. For example, in healthcare, AI-powered diagnostic tools analyze medical images, predict patient outcomes, and streamline administrative tasks, allowing healthcare professionals to dedicate more time to patient care and complex decision-making. Similarly, in finance, AI automates fraud detection, credit scoring, and customer support through chatbots, allowing financial experts to innovate new investment strategies and build stronger client relationships. In logistics, AI optimizes supply chains, predicts disruptions, and automates warehouse operations, empowering human workers to develop sustainable practices and enhance customer service. Why Pursue Artificial Intelligence as a Career ? The AI industry is undeniably exciting, but beyond its initial allure lies a multitude of compelling reasons to pursue a career in this field: Unparalleled demand: The AI job market is expanding at an exponential rate, and more AI-related jobs are being posted on job sites than ever before. Companies are investing heavily in AI solutions to stay competitive, creating a surge in demand. The AI job market is expanding at an exponential rate, and more are being posted on job sites than ever before. Companies are investing heavily in AI solutions to stay competitive, creating a surge in demand. Competitive salaries: AI-related roles are among the highest-paying in the tech industry. For example, machine learning engineers earn an average salary of $161,522 annually in the U.S. AI-related roles are among the highest-paying in the tech industry. For example, machine learning engineers earn an annually in the U.S. Opportunities for impact: AI careers offer opportunities to work on cutting-edge technologies, solve global challenges, and make a meaningful impact on society AI careers offer opportunities to work on cutting-edge technologies, solve global challenges, and make a meaningful impact on society Industry versatility: AI professionals can explore diverse industries, from healthcare and robotics to entertainment and finance, providing career flexibility and growth opportunities With these powerful benefits, artificial intelligence career paths offer excitement and ample opportunities for growth, success, and real-world impact. Essential Skills and Qualifications for AI-Related Jobs Careers in artificial intelligence and robotics require a blend of technical expertise and soft skills. Professionals in this field must understand cutting-edge technologies while also possessing the ability to apply them effectively in various industries. Below are the key areas of knowledge required to thrive in AI-related roles. Machine Learning (ML) Machine learning forms the foundation of most AI applications. Professionals must understand algorithms such as supervised learning, unsupervised learning, and reinforcement learning, which allow machines to learn from data and improve performance over time. Tools like TensorFlow and PyTorch are indispensable for building, training, and deploying ML models effectively. Deep Learning (DL) Deep learning involves using advanced neural networks to solve complex problems. Mastery of architectures like convolutional neural networks (CNNs) for image processing and recurrent neural networks (RNNs) for sequential data is essential. These skills are critical for developing applications such as autonomous vehicles, facial recognition, and advanced natural language processing tools. Data Analysis and Visualization Data analysis is at the heart of AI, as clean and interpretable data is crucial for building accurate models. Professionals in artificial intelligence-related jobs like data analysis must know how to clean, process, and analyze datasets to extract meaningful insights. Visualization tools like Tableau and Power BI, along with programming libraries such as Pandas and Matplotlib in Python, help present data in a way that drives better decision-making. Natural Language Processing (NLP) Natural language processing enables machines to interact with human language, making it a critical skill for AI applications like chatbots and virtual assistants. Familiarity with libraries such as spaCy, NLTK, and Hugging Face Transformers is crucial in building effective language models. These tools are important for tasks like text classification, sentiment analysis, and machine translation. Robotics and Automation AI plays a significant role in robotics by integrating sensors, movement algorithms, and perception technologies. This combination allows robots to perform tasks autonomously, such as assembling products on manufacturing lines or assisting in medical surgeries. Professionals must understand both hardware and software aspects of robotics to design intelligent and adaptable systems. Computer Vision (CV) Computer vision involves extracting and analyzing information from visual data, such as images and videos. Applications include facial recognition systems, augmented reality experiences, and autonomous vehicle navigation. Proficiency in tools like OpenCV and frameworks such as TensorFlow or PyTorch is crucial for developing robust computer vision solutions. Cloud Computing and AI Deployment AI models require significant computational resources for training and deployment, often necessitating the use of cloud platforms. Services like AWS, Azure, and Google Cloud provide scalable infrastructure to store data, manage computing power, and deploy AI solutions. Programming Languages (Python, R, and SQL) Programming is a fundamental skill for any AI professional. Python is widely used for AI model development due to its simplicity and extensive library support, while R is valuable for statistical analysis and visualization. SQL is critical for managing and querying large datasets, making it an essential tool for data-driven decision-making in AI projects. Big Data Management The ability to manage and analyze massive datasets is crucial for AI applications. Tools like Hadoop and Apache Spark enable the processing of large volumes of data in distributed environments. Additionally, NoSQL databases provide flexible storage solutions for unstructured data, making them invaluable for handling complex AI workflows. Mathematics and Statistics A strong foundation in mathematics and statistics is necessary to understand and develop AI algorithms. Linear algebra and calculus underpin neural networks and optimization techniques, while probability and statistics are critical for interpreting data and building predictive models. 16 Artificial Intelligence-Related Jobs Employment in computer and information technology occupations is expected to grow significantly faster than the average for all professions between 2023 and 2033. According to the U.S. Bureau of Labor Statistics, these fields are projected to offer approximately 356,700 job openings annually. If you’re interested in this growing industry, keep reading for information on 16 exciting artificial intelligence career paths. 1. Machine Learning Engineer Machine learning engineers develop and deploy algorithms that allow machines to learn from data and make decisions without explicit programming. They work on projects such as recommendation systems, predictive analytics, and fraud detection. This role requires strong programming skills, knowledge of frameworks like TensorFlow and PyTorch, and expertise in data structures and algorithm optimization. 2. Data Scientist Data scientists analyze and interpret complex datasets to uncover actionable insights that inform business decisions. They use machine learning models to predict trends, optimize operations, and drive innovation. Proficiency in programming languages like Python and R, as well as expertise in visualization tools such as Tableau, is required for success in this role. 3. Data Mining and Analysis Professionals in data mining and analysis extract meaningful patterns and trends from large datasets. This role involves using machine learning techniques and statistical methods to uncover insights that improve decision-making processes. Tools like SQL, Hadoop, and Apache Spark are critical for managing and analyzing vast amounts of data efficiently. 4. AI Research Scientist AI research scientists push the boundaries of AI technologies by conducting experiments and developing innovative algorithms. They often specialize in fields like applied mathematics, deep learning, and computational statistics. An advanced degree in computer science or a related field is typically required, along with hands-on experience in research and development. 5. AI FinTech Developer What are the jobs related to AI in finance? AI FinTech developers design and implement AI solutions for financial technology applications, such as fraud detection, credit scoring, and personalized financial planning. They use machine learning models to process vast amounts of financial data and provide actionable insights. Knowledge of financial systems and programming expertise in Python or Java are vital for this role. 6. AI Product Manager AI product managers act as the bridge between technical teams and business stakeholders, ensuring the successful development and deployment of AI products. They oversee the product life cycle, from ideation to implementation, aligning technical capabilities with business goals. This role requires excellent communication skills, strategic thinking, and a strong understanding of AI technologies. 7. Robotics Engineer Robotics engineers design, build, and program robots to perform tasks autonomously. They integrate AI technologies to enhance robot functionality, enabling applications such as warehouse automation, surgical robots, and self-driving vehicles. Key skills include robotics programming, sensor integration, and knowledge of machine learning algorithms. 8. Computer Vision Engineer Computer vision engineers develop systems that analyze and interpret visual data from the real world. They work on applications such as facial recognition, augmented reality, and autonomous vehicles. Expertise in image processing, deep learning, and tools like OpenCV and TensorFlow are needed for a future in this role. 9. NLP Engineer What kind of AI jobs involve language processing? Natural Language Processing (NLP) engineers create systems that interact with human language, powering tools like chatbots, translation services, and sentiment analysis software. This role requires skills in text mining and machine learning and familiarity with NLP libraries like spaCy and Hugging Face. These engineers bridge the gap between machine learning models and linguistic understanding. 10. AI Ethics Specialist AI ethics specialists ensure that AI systems are developed and used responsibly. They address ethical concerns such as bias, fairness, and privacy, helping organizations align their AI practices with societal and legal expectations. This role demands knowledge of AI ethics frameworks, regulatory awareness, and strong problem-solving skills. 11. Business Intelligence (BI) Developer with AI Focus BI developers specializing in AI use machine learning models to extract insights from data and support strategic business decisions. They design dashboards, automate reporting processes, and leverage predictive analytics to enhance decision-making. Proficiency in Power BI, Tableau, and SQL is critical for delivering impactful BI solutions. 12. AI Hardware Engineer AI hardware engineers design specialized hardware, such as GPUs and AI accelerators (such as Google’s Tensor Processing Units), to optimize the performance of AI algorithms. They work closely with AI researchers to develop efficient computing systems that handle complex models. Skills in circuit design, hardware simulation tools, and knowledge of neural network architecture are crucial for this role. 13. AI Software Engineer AI software engineers develop applications that integrate AI functionalities, such as recommendation systems, speech recognition, and automated decision-making tools. They ensure the seamless integration of AI models into software products, focusing on scalability and user experience. This role requires strong programming skills, particularly in Python, Java, or C++. 14. UX Designer UX designers leverage AI to create intuitive and personalized user experiences. They use AI tools to analyze user behavior and optimize interface designs for efficiency and satisfaction. This role blends creativity with technical skills, requiring expertise in design software and an understanding of AI-driven user insights. 15. UX Developer UX developers bring AI-enhanced user experience designs to life by implementing functionality and interactivity in digital products. They work closely with designers and software engineers to ensure seamless user interfaces. Proficiency in front-end development and knowledge of AI integration are critical for this position. 16. Algorithm Developer The last job on our AI jobs list is an algorithm developer. Algorithm developers design and refine the algorithms that power AI systems, ensuring they are efficient, accurate, and scalable. They play a critical role in creating the mathematical models and logic that drive machine learning and decision-making processes. This role requires expertise in data structures, optimization techniques, and programming languages. Starting Your AI Career Path A career in artificial intelligence can be both exciting and rewarding. To get started, consider a well-rounded journey that combines education, practical experience, and networking. Below is a guide to help you get started. Educational Pathways The first step in pursuing a career in AI is obtaining the right education. Degrees in fields like computer science, data science, or artificial intelligence provide a solid foundation in programming, algorithms, and data analysis. Specialized programs focused on AI and machine learning can further enhance your expertise and make you more competitive in the job market. In addition to traditional degrees, online courses and certifications can supplement your knowledge and keep you updated with the latest advancements. Many programs are available on topics such as machine learning, deep learning, and natural language processing. Certifications from industry leaders also demonstrate your commitment to mastering AI technologies. At California Miramar University (CMU), you can gain a comprehensive education in AI through our specialized programs: Bachelor of Science in Business Administration with an AI Focus : This undergraduate program integrates AI concepts with business principles, preparing students for leadership roles in technology-driven industries This undergraduate program integrates AI concepts with business principles, preparing students for leadership roles in technology-driven industries Master of Science in Artificial Intelligence : This advanced degree dives deep into AI technologies, offering hands-on experience and in-depth knowledge to excel in specialized AI roles Gaining Practical Experience While education lays the groundwork for a career in AI, hands-on experience is key to applying that knowledge in practical settings. Participating in internships is an excellent way to gain exposure to real-world projects and industry practices. Working under experienced professionals not only helps you build technical skills but also provides valuable insights into how AI solutions are implemented in businesses. Personal projects are another powerful way to demonstrate your expertise. By creating AI models, chatbots, or predictive tools, you can showcase your problem-solving skills and creativity. Sharing these projects on platforms like GitHub helps build your professional portfolio and attracts potential employers. Building a Professional Network Networking is a vital step in advancing your career, especially in a dynamic field like AI. Attending conferences and workshops like NeurIPS and ICML provides opportunities to learn from industry leaders and engage with professionals at the forefront of AI innovation. Online communities on platforms like LinkedIn, Reddit, and Kaggle offer another avenue for building relationships and sharing knowledge. Engaging in discussions, contributing insights, and showcasing your work can establish your presence in the AI field. Begin Your Artificial Intelligence Career Path with CMU AI offers exciting opportunities to shape the future across industries like healthcare, finance, and robotics. With the right education and skills, you can unlock high-paying roles and leadership positions. A Master’s degree in Artificial Intelligence can be a game-changer, providing advanced knowledge and practical experience to excel in this competitive field. At California Miramar University (CMU), programs like the Bachelor of Science in Business Administration with AI focus, the Master of Business Administration in Artificial Intelligence, and the Master of Science in Artificial Intelligence equip students with the expertise to thrive in AI careers. Explore CMU’s programs today and start your journey toward a successful AI career. AI-Related Jobs : FAQs Do you still have questions about AI careers? Here are answers to common questions. For more details, contact us for personalized guidance. How do I start a career in AI? Start with a degree in computer science, data science, or AI. Gain hands-on experience through internships, projects, and open-source contributions, and build your network. What technical skills are in demand for AI careers? In-demand skills include: Machine learning and deep learning Programming (Python, R, SQL) Data analysis and visualization Natural language processing (NLP) Big data management and cloud computing How can I gain experience in AI? Seek internships, develop personal projects, and contribute to open-source initiatives or research to gain practical knowledge. What industries use AI? The applications of AI technology are vast. AI is widely adopted in industries like healthcare, finance, retail, and transportation.
2022-12-01T00:00:00
https://www.calmu.edu/news/artificial-intelligence-career-paths
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JobCopilot: Automate Job Applications with AI
Automate Job Applications with AI
https://jobcopilot.com
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Get 10X more Job Interviews with JobCopilot. Automatically apply to jobs from 300000+ companies worldwide. Try it today!
The average person needs to apply to 50 – 100 jobs just to get 1 interview – that takes a lot of time if you do it manually! With JobCopilot, you can send up to 50 personalized job applications per day! That multiplies the number of interviews you get every month.
2022-12-01T00:00:00
https://jobcopilot.com/?
[ { "date": "2022/12/01", "position": 48, "query": "AI employment" }, { "date": "2023/01/01", "position": 57, "query": "AI employment" }, { "date": "2023/02/01", "position": 45, "query": "AI employment" } ]
Jobs in AI and watsonx | IBM Careers
Jobs in AI and watsonx
https://www.ibm.com
[]
As a Backend Developer, you will be part of a global team that builds and supports IBM Watson® Machine Learning and watsonx.ai™. Available jobs.
We empower our IBMers to exemplify behavior that fosters a culture of conscious inclusion and belonging, where innovation can thrive. We're dedicated to promoting, advancing and celebrating the plurality of thought from those of all backgrounds and experiences.
2022-12-01T00:00:00
https://www.ibm.com/careers/ai-and-watsonx
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Your employees, on AI - Sintra
Your employees, on AI
https://sintra.ai
[]
Your helpers that never sleep. · Build, grow, and scale your business with a team of AI helpers. Get Sintra.
Hiring Sintra was a great decision for my struggling boutique. They handle social media posts, guide my ads, and even offered a solution for double social media pages. Now I can focus on my inventory and customers. I once had a large team, and although I loved my helpers, they needed constant motivation. With Sintra, there’s no drama, just new ideas that I can simply accept or reject. It’s a huge relief—100% recommended. As an entrepreneur launching a new venture, Sintra.ai has made a real difference. The AI assistants are like personal staff I can rely on. And whenever I needed support, the team was on point. A must-try for any budding business! Each AI bot tackles my to-do list, from scheduling tasks to crawling my website for SEO tips. I love how it set up calendar reminders for all my commitments. Sintra.ai is well worth every penny, especially for a busy single-person business. I can’t recommend SintraAI enough. It’s like having a personal business coach 24/7, mapping out steps to grow my company and clarifying my priorities. I feel a renewed sense of focus and control every day. SintraAI has been a Game-Changer for My Business! Sintra X Saved Me Time Signed up for Sintra X—it felt overwhelming at first, but once it understood how I think, it turned into a creative powerhouse. Support is top-notch, and the daily integrations impress me. Dec 10, 2024 • Sami Liftoff • US Some Time They’re Too Effective with Ideas I’m not usually one to give top marks, but once I got comfortable with Sintra’s 12 helpers, I was blown away by their efficiency. They churn out so many analytical ideas I have to pause and digest them. It’s sometimes overwhelming, but in a good way. December 29, 2024 • lars • DK SOOO much better than ChatGPT Sintra integrates with all my favorite tools and these little helpers automate my tasks in a huge way. They actually learn my company’s style day by day. It’s a massive step up from generic AI chats. December 30, 2024 • Michelangelo • IT So far, I love it! My life is simpler with Sintra. It handles content creation, next steps, brainstorming, and copy. I highly recommend it if you want to free up mental space for what truly matters in your business. December 28, 2024 • Lionel D'Alvia • US
2022-12-01T00:00:00
https://sintra.ai/
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AI & Machine Learning Careers | Lockheed Martin
AI & Machine Learning Careers
https://www.lockheedmartin.com
[]
Explore open jobs in AI & Machine Learning. AI & Machine Learning Careers Behind some of the most advanced autonomous systems and technologies.
Lockheed Martin utilizes our own internal Talent Acquisition Organization to fill our employment needs. If you are contacted over the phone or e-mailed, by a company listing a Lockheed Martin job and requesting your personal information, allegedly on Lockheed Martin's behalf, please do not respond. Lockheed Martin is an equal opportunity employer. Qualified candidates will be considered without regard to legally protected characteristics. Know Your Rights (opens in a new window) | Accommodations (opens in a new window) www.dhs.gov/E-Verify E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.
2022-12-01T00:00:00
https://www.lockheedmartin.com/en-us/careers/career-areas/ai.html
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Job Application for AI Tutor (Full-Time) at xAI - Greenhouse
AI Tutor (Full-Time)
http://job-boards.greenhouse.io
[]
All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently ...
xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All engineers and researchers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. The AI Tutor role is a remote, full-time, temporary position expected to last approximately 6 months (with potential for extension based on project goals and business needs). AI Tutor’s Role in Advancing xAI’s Mission: As an AI Tutor, you will play an essential role in advancing xAI's mission by supporting the training and refinement of xAI’s AI models. AI Tutors teach our AI models about how people interact and react, as well as about how people approach issues and discussions. To accomplish this, AI Tutors will actively participate in gathering or providing data, such as text, voice, and video data, sometimes providing annotations, recording audio, or participating in video sessions. We seek individuals who are comfortable and eager to engage in these activities as a fundamental part of the role, ensuring a strong alignment with xAI’s goals and objectives to innovate. Scope: An AI Tutor will provide services that include labeling and annotating data in text, voice, and video formats to support AI model training. At times, this may involve recording audio or video sessions, and tutors are expected to be comfortable with these tasks as they are fundamental to the role. Such data is a job requirement to advance xAI’s mission, and AI Tutors acknowledge that all work is done for hire and owned by xAI. Responsibilities: Use proprietary software applications to provide input/labels on defined projects. Support and ensure the delivery of high-quality curated data. Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies. Interact with the technical staff to help improve the design of efficient annotation tools. Engage in diverse writing assignments to refine generative AI models. Key Qualifications: Proficiency in reading and writing, both in informal and professional English. Strong research skills, and the ability to navigate various information resources, databases, and online resources are essential. You display outstanding communication, interpersonal, analytical, and organizational capabilities. Solid reading comprehension skills combined with capacity to exercise autonomous judgment even when presented with limited data/material. You have a strong passion for and commitment to technological advancements and innovation. Preferred Qualifications: In addition to English, you have proficiency in reading and writing in Korean, Vietnamese, Chinese, German, Russian, Italian, French, Arabic, Indonesian, Turkish, Hindi, Persian, Spanish, and/or Portuguese You possess experience in technical writing, journalism, or a professional writing setting. Location, Hourly, and Other Expectations: This position is fully remote. We are unable to provide visa sponsorship. If you are based in the US, please note we are unable to hire in the states of Wyoming and Illinois at this time. Team members are expected to work from 9:00 am - 5:30 pm PST for the first two weeks of training and 9:00am - 5:30pm in their own timezone thereafter. For those who will be working from a personal device, please note your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later. You must own and have reliable access to a smartphone. Compensation and Benefits:
2022-12-01T00:00:00
http://job-boards.greenhouse.io/xai/jobs/4595198007
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United States, Software and Services: Machine Learning and AI - Jobs
United States, Software and Services: Machine Learning and AI
https://jobs.apple.com
[]
Explore all jobs at Apple. Search by keyword, location, and other criteria. Create a profile and apply today.
Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Bring passion and dedication to your job and there’s no telling what you could accomplish. Do you want to be a part of A...
2022-12-01T00:00:00
https://jobs.apple.com/en-us/search?location=united-states-USA&team=machine-learning-and-ai-SFTWR-MCHLN
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Boost Your Outbound Sales with an AI BDR from Artisan
Boost Your Outbound Sales with an AI BDR from Artisan
https://www.artisan.co
[]
Artisan automates your outbound with an all-in-one, AI-first platform powered by AI employees. Get better outbound sales results with an AI BDR.
Automate Your Outbound With an AI-First Platform Powered by AI Employees Equip your team with the best-in-class outbound tools and our AI BDR Ava, who automates your entire outbound workflow.
2022-12-01T00:00:00
https://www.artisan.co/
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AI-Assisted Recruiting With Paychex Recruiting Copilot
AI-Assisted Recruiting With Paychex Recruiting Copilot
https://www.paychex.com
[]
Explore how automated recruiting with AI-powered tools can enhance your hiring efficiency, streamline candidate sourcing and talent acquisition.
Hire up to 5x Faster* With AI‑Assisted Recruiting Skip the job postings. Describe your employment needs and let Paychex Recruiting Copilot, in partnership with Findem, deliver talent to you. Sign up and get your first 3 profiles in seconds—absolutely free.
2022-12-01T00:00:00
https://www.paychex.com/hiring/ai-assisted-recruiting
[ { "date": "2022/12/01", "position": 64, "query": "AI employment" }, { "date": "2023/01/01", "position": 4, "query": "AI hiring" }, { "date": "2023/01/01", "position": 74, "query": "AI employment" }, { "date": "2023/02/01", "position": 4, "query": "AI hiring" }, { "date": "2023/02/01", "position": 62, "query": "AI employment" }, { "date": "2023/03/01", "position": 4, "query": "AI hiring" }, { "date": "2023/04/01", "position": 54, "query": "AI employment" }, { "date": "2023/05/01", "position": 59, "query": "AI employment" }, { "date": "2023/06/01", "position": 52, "query": "AI employment" }, { "date": "2023/06/01", "position": 4, "query": "AI hiring" }, { "date": "2023/08/01", "position": 50, "query": "AI employment" }, { "date": "2023/08/01", "position": 4, "query": "AI hiring" }, { "date": "2023/09/01", "position": 4, "query": "AI hiring" }, { "date": "2023/11/01", "position": 60, "query": "AI employment" }, { "date": "2023/12/01", "position": 57, "query": "AI employment" }, { "date": "2023/12/01", "position": 4, "query": "AI hiring" }, { "date": "2024/01/01", "position": 54, "query": "AI employment" }, { "date": "2024/01/01", "position": 4, "query": "AI hiring" }, { "date": "2024/02/01", "position": 67, "query": "AI employment" }, { "date": "2024/06/01", "position": 51, "query": "AI employment" }, { "date": "2024/06/01", "position": 4, "query": "AI hiring" }, { "date": "2024/07/01", "position": 58, "query": "AI employment" }, { "date": "2024/10/01", "position": 4, "query": "AI hiring" }, { "date": "2024/11/01", "position": 60, "query": "AI employment" }, { "date": "2025/01/01", "position": 74, "query": "AI employment" }, { "date": "2025/01/01", "position": 4, "query": "AI hiring" }, { "date": "2025/02/01", "position": 52, "query": "AI employment" }, { "date": "2025/02/01", "position": 6, "query": "AI hiring" }, { "date": "2025/03/01", "position": 58, "query": "AI employment" }, { "date": "2025/04/01", "position": 6, "query": "AI hiring" }, { "date": "2025/05/01", "position": 63, "query": "AI employment" }, { "date": "2025/06/01", "position": 59, "query": "AI employment" }, { "date": "2025/06/01", "position": 6, "query": "AI hiring" } ]
Careers \ Anthropic
Careers \ Anthropic
https://www.anthropic.com
[]
... employees is crucial to our collective success and wellbeing. ... We work to inspire a 'race to the top' dynamic where AI developers must compete to develop the ...
The novel challenges we think about at Anthropic demand diverse expertise and perspectives. Our interview process is designed to identify thoughtful candidates who bring unique strengths to our multidisciplinary team. If you think this may describe you, we’d love to hear from you regardless of your background or experience. One of the most common questions we get is about whether it is worth applying to work at Anthropic if you have not worked on modern machine learning systems in the past. Yes! For some roles, ML experience is expected, but many technical staff have arrived at Anthropic with no machine learning experience. If you aren’t sure about the ML experience needed for your role, ask your recruiter. We use shared environments like Colab and Replit for our programming-focused interviews. We’ll be very interested in how you think through each problem and analyze the tradeoffs between possible approaches, and we’ll also expect you to write, run, and debug your solutions. You’ll be allowed to look things up in documentation or on the web, just like you usually can (which is why we’ll ask you to share your screen throughout each interview); but it’s still important to be familiar with basic syntax, standard libraries, and common idioms in the language you’re interviewing in, so that looking things up doesn’t consume too much time. Your interview process will also include non-technical questions about your experience and what motivates you, and, of course, you’ll have time to ask us about Anthropic! We can’t wait to meet you.
2022-12-01T00:00:00
https://www.anthropic.com/careers
[ { "date": "2022/12/01", "position": 65, "query": "AI employment" }, { "date": "2023/01/01", "position": 47, "query": "AI employment" }, { "date": "2023/02/01", "position": 63, "query": "AI employment" }, { "date": "2023/03/08", "position": 83, "query": "artificial intelligence employment" }, { "date": "2023/03/08", "position": 37, "query": "artificial intelligence hiring" }, { "date": "2023/04/01", "position": 56, "query": "AI employment" }, { "date": "2023/05/01", "position": 56, "query": "AI employment" }, { "date": "2023/06/01", "position": 56, "query": "AI employment" }, { "date": "2023/08/01", "position": 56, "query": "AI employment" }, { "date": "2023/11/01", "position": 57, "query": "AI employment" }, { "date": "2023/12/01", "position": 58, "query": "AI employment" }, { "date": "2024/01/01", "position": 56, "query": "AI employment" }, { "date": "2024/02/01", "position": 64, "query": "AI employment" }, { "date": "2024/06/01", "position": 59, "query": "AI employment" }, { "date": "2024/07/01", "position": 57, "query": "AI employment" }, { "date": "2024/11/01", "position": 59, "query": "AI employment" }, { "date": "2025/01/01", "position": 57, "query": "AI employment" }, { "date": "2025/02/01", "position": 58, "query": "AI employment" }, { "date": "2025/02/01", "position": 57, "query": "AI hiring" }, { "date": "2025/03/01", "position": 65, "query": "AI employment" }, { "date": "2025/05/01", "position": 65, "query": "AI employment" }, { "date": "2025/06/01", "position": 62, "query": "AI employment" } ]
Careers | MagicSchool - Magic School AI
MagicSchool
https://www.magicschool.ai
[]
Explore careers with MagicSchool AI in engineering, product, marketing, sales, and more ... We work hard for our teachers and encourage our employees to rest and ...
Educators are Magic Educators are at the heart of the educational process - they are the magic, not the AI. We use AI to help educators be more efficient, personalize instruction, and amplify their impact in service of their students. Responsible AI for Students We believe in teaching students to use AI responsibly - not as a replacement for their thinking. We empower educators to create engaging, innovative AI-driven experiences that support student learning, creativity, and readiness for their future. Outcomes-Driven We focus on tools that deliver real impact and accelerate the priorities of educators, schools, and districts in service of student outcomes. Community We foster a community of educators during a time of rapid technological change. We listen to them and serve their needs. Education First We are focused on the application of the latest technologies to the challenges in education. We will always seek to add to our platform in the ways it can make the greatest impact in education.
2022-12-01T00:00:00
https://www.magicschool.ai/careers
[ { "date": "2022/12/01", "position": 67, "query": "AI employment" }, { "date": "2023/01/01", "position": 37, "query": "AI employment" }, { "date": "2023/02/01", "position": 60, "query": "AI employment" }, { "date": "2025/02/01", "position": 68, "query": "AI employment" }, { "date": "2025/03/01", "position": 64, "query": "AI employment" }, { "date": "2025/04/24", "position": 33, "query": "AI employment" }, { "date": "2025/05/01", "position": 66, "query": "AI employment" }, { "date": "2025/06/01", "position": 61, "query": "AI employment" } ]
Open jobs | micro1
Open jobs
https://www.micro1.ai
[]
micro1 is SOC 2, Type 1 compliant. 3000 El Camino Real Palo Alto, CA 94306. © 2025 micro1 Inc. by using micro1.ai, you accept our cookie policy. Accept.
Zara AI recruiter agent to identify and hire the best talent on earth
2022-12-01T00:00:00
https://www.micro1.ai/jobs
[ { "date": "2022/12/01", "position": 68, "query": "AI employment" }, { "date": "2023/01/01", "position": 34, "query": "AI employment" }, { "date": "2023/02/01", "position": 65, "query": "AI employment" }, { "date": "2025/02/01", "position": 65, "query": "AI employment" }, { "date": "2025/03/01", "position": 66, "query": "AI employment" }, { "date": "2025/05/01", "position": 67, "query": "AI employment" }, { "date": "2025/06/01", "position": 65, "query": "AI employment" } ]
Conversational hiring software that gets work done for you — Paradox
Conversational hiring software that gets work done for you — Paradox
https://www.paradox.ai
[]
What else can your AI assistant do? · Indeed Apply. Supercharge every Indeed application. · Personalization. Build an assistant that's tailored to you. · Surveys.
Hiring takes time. But our AI assistant Olivia gives you more of it — automating tasks so you spend more time with people, not software.
2022-12-01T00:00:00
https://www.paradox.ai/
[ { "date": "2022/12/01", "position": 69, "query": "AI employment" }, { "date": "2022/12/01", "position": 26, "query": "artificial intelligence hiring" }, { "date": "2023/01/01", "position": 6, "query": "AI hiring" }, { "date": "2023/01/01", "position": 82, "query": "AI employment" }, { "date": "2023/02/01", "position": 6, "query": "AI hiring" }, { "date": "2023/02/01", "position": 66, "query": "AI employment" }, { "date": "2023/03/01", "position": 6, "query": "AI hiring" }, { "date": "2023/04/01", "position": 59, "query": "AI employment" }, { "date": "2023/05/01", "position": 57, "query": "AI employment" }, { "date": "2023/05/01", "position": 22, "query": "artificial intelligence hiring" }, { "date": "2023/06/01", "position": 59, "query": "AI employment" }, { "date": "2023/06/01", "position": 5, "query": "AI hiring" }, { "date": "2023/06/01", "position": 93, "query": "artificial intelligence hiring" }, { "date": "2023/08/01", "position": 59, "query": "AI employment" }, { "date": "2023/08/01", "position": 3, "query": "AI hiring" }, { "date": "2023/09/01", "position": 3, "query": "AI hiring" }, { "date": "2023/10/01", "position": 25, "query": "artificial intelligence hiring" }, { "date": "2023/11/01", "position": 58, "query": "AI employment" }, { "date": "2023/12/01", "position": 60, "query": "AI employment" }, { "date": "2023/12/01", "position": 5, "query": "AI hiring" }, { "date": "2024/01/01", "position": 57, "query": "AI employment" }, { "date": "2024/01/01", "position": 3, "query": "AI hiring" }, { "date": "2024/02/01", "position": 73, "query": "AI employment" }, { "date": "2024/03/01", "position": 22, "query": "artificial intelligence hiring" }, { "date": "2024/04/01", "position": 24, "query": "artificial intelligence hiring" }, { "date": "2024/05/01", "position": 23, "query": "artificial intelligence hiring" }, { "date": "2024/06/01", "position": 61, "query": "AI employment" }, { "date": "2024/06/01", "position": 3, "query": "AI hiring" }, { "date": "2024/07/01", "position": 61, "query": "AI employment" }, { "date": "2024/10/01", "position": 3, "query": "AI hiring" }, { "date": "2024/10/01", "position": 29, "query": "artificial intelligence hiring" }, { "date": "2024/11/01", "position": 61, "query": "AI employment" }, { "date": "2024/11/14", "position": 6, "query": "AI hiring" }, { "date": "2025/01/01", "position": 88, "query": "AI employment" }, { "date": "2025/01/01", "position": 3, "query": "AI hiring" }, { "date": "2025/01/01", "position": 23, "query": "artificial intelligence hiring" }, { "date": "2025/02/01", "position": 67, "query": "AI employment" }, { "date": "2025/02/01", "position": 5, "query": "AI hiring" }, { "date": "2025/03/01", "position": 63, "query": "AI employment" }, { "date": "2025/04/01", "position": 4, "query": "AI hiring" }, { "date": "2025/05/01", "position": 64, "query": "AI employment" }, { "date": "2025/06/01", "position": 60, "query": "AI employment" }, { "date": "2025/06/01", "position": 5, "query": "AI hiring" }, { "date": "2025/06/01", "position": 21, "query": "artificial intelligence hiring" } ]
Braintrust | Transforming Hiring with AI Recruiting
Transforming Hiring with AI Recruiting
https://www.usebraintrust.com
[]
AI-Powered interviews to help you hire faster. Reduce costs, eliminate bias, and identify top talent quickly.
“We've been looking for any solution that would help us battle fake candidates and figure out where to focus our time. Braintrust AIR is the best product on the market we've seen.”
2022-12-01T00:00:00
https://www.usebraintrust.com/
[ { "date": "2022/12/01", "position": 74, "query": "AI employment" }, { "date": "2023/01/01", "position": 58, "query": "AI employment" }, { "date": "2023/02/01", "position": 69, "query": "AI employment" }, { "date": "2023/04/01", "position": 62, "query": "AI employment" }, { "date": "2023/05/01", "position": 61, "query": "AI employment" }, { "date": "2023/06/01", "position": 65, "query": "AI employment" }, { "date": "2023/08/01", "position": 65, "query": "AI employment" }, { "date": "2023/09/01", "position": 9, "query": "AI hiring" }, { "date": "2023/11/01", "position": 65, "query": "AI employment" }, { "date": "2023/12/01", "position": 63, "query": "AI employment" }, { "date": "2023/12/01", "position": 8, "query": "AI hiring" }, { "date": "2024/01/01", "position": 68, "query": "AI employment" }, { "date": "2024/02/01", "position": 74, "query": "AI employment" }, { "date": "2024/06/01", "position": 66, "query": "AI employment" }, { "date": "2024/06/01", "position": 8, "query": "AI hiring" }, { "date": "2024/07/01", "position": 65, "query": "AI employment" }, { "date": "2024/10/01", "position": 8, "query": "AI hiring" }, { "date": "2024/11/01", "position": 64, "query": "AI employment" }, { "date": "2025/01/01", "position": 62, "query": "AI employment" }, { "date": "2025/02/01", "position": 70, "query": "AI employment" }, { "date": "2025/02/18", "position": 80, "query": "AI wages" }, { "date": "2025/03/01", "position": 69, "query": "AI employment" }, { "date": "2025/05/01", "position": 69, "query": "AI employment" }, { "date": "2025/06/01", "position": 72, "query": "AI employment" } ]
Careers | Thatch
Careers
https://thatch.ai
[]
We're hiring a Technical Program Manager to lead internal AI adoption at Thatch. You'll define and drive the AI strategy across every team, helping us work ...
Work with meaning Our long-term vision is to be the default way companies provide health benefits. We believe we have a unique opportunity to make a positive impact on the lives of millions of people by making healthcare more accessible and affordable. We’re intensely focused on happiness at Thatch and committed to creating an environment where everyone can do their best work. In addition to everything listed here, you’ll get to work with passionate people who care deeply about the mission and each other.
2022-12-01T00:00:00
https://thatch.ai/jobs
[ { "date": "2022/12/01", "position": 77, "query": "AI employment" }, { "date": "2022/12/01", "position": 93, "query": "AI wages" }, { "date": "2023/01/01", "position": 83, "query": "AI employment" }, { "date": "2023/02/01", "position": 72, "query": "AI employment" }, { "date": "2023/02/09", "position": 36, "query": "AI wages" }, { "date": "2023/04/01", "position": 69, "query": "AI employment" }, { "date": "2023/05/01", "position": 68, "query": "AI employment" }, { "date": "2023/06/01", "position": 69, "query": "AI employment" }, { "date": "2023/08/01", "position": 68, "query": "AI employment" }, { "date": "2023/11/01", "position": 71, "query": "AI employment" }, { "date": "2023/12/01", "position": 70, "query": "AI employment" }, { "date": "2024/01/01", "position": 72, "query": "AI employment" }, { "date": "2024/02/01", "position": 80, "query": "AI employment" }, { "date": "2024/06/01", "position": 73, "query": "AI employment" }, { "date": "2024/07/01", "position": 71, "query": "AI employment" }, { "date": "2024/11/01", "position": 71, "query": "AI employment" }, { "date": "2025/01/01", "position": 68, "query": "AI employment" } ]
If AI could run a business more efficiently than any human ... - Reddit
The heart of the internet
https://www.reddit.com
[]
Would this improve productivity and innovation, or undermine human employment and creativity? Could we trust such AI with legal, ethical, and ...
Imagine an AI system that can outperform even the best human teams at running an entire business - from operations and customer support to marketing and financial planning. It doesn't take breaks, doesn't need motivation, and continuously self-optimizes based on real-time data. If this kind of AI were available today, should we allow it to fully manage a business with little to no human oversight? Some questions to consider: Would this improve productivity and innovation, or undermine human employment and creativity? Could we trust such AI with legal, ethical, and regulatory decisions? Should there be limits or legal frameworks to keep AI-managed businesses accountable? Is it ethical to let AI systems accumulate capital and power with minimal human input? Would love to hear how others - developers, entrepreneurs, or just curious observers - see the trade-offs. Where should we draw the line?
2022-12-01T00:00:00
https://www.reddit.com/r/ChatGPT/comments/1ltrrqi/if_ai_could_run_a_business_more_efficiently_than/
[ { "date": "2022/12/01", "position": 79, "query": "AI employment" }, { "date": "2023/02/01", "position": 75, "query": "AI employment" } ]
Careers - build the future - Mistral AI
Careers - build the future
https://mistral.ai
[]
Transportation with a “forfait mobilités durables” of 600€ per year. Childcare with nursery seats reserved for employees. Apply now. Resources. chat-orange.
At the heart of our culture is a strong sense of connection and celebration. We believe in fostering meaningful relationships and creating memorable experiences for our team.
2022-12-01T00:00:00
https://mistral.ai/careers
[ { "date": "2022/12/01", "position": 80, "query": "AI employment" }, { "date": "2023/01/01", "position": 78, "query": "AI employment" }, { "date": "2023/02/01", "position": 80, "query": "AI employment" }, { "date": "2023/04/01", "position": 74, "query": "AI employment" }, { "date": "2023/05/01", "position": 77, "query": "AI employment" }, { "date": "2023/06/01", "position": 75, "query": "AI employment" }, { "date": "2023/08/01", "position": 73, "query": "AI employment" }, { "date": "2023/11/01", "position": 77, "query": "AI employment" }, { "date": "2023/12/01", "position": 71, "query": "AI employment" }, { "date": "2024/01/01", "position": 78, "query": "AI employment" }, { "date": "2024/02/01", "position": 81, "query": "AI employment" }, { "date": "2024/06/01", "position": 77, "query": "AI employment" }, { "date": "2024/07/01", "position": 77, "query": "AI employment" }, { "date": "2024/11/01", "position": 79, "query": "AI employment" }, { "date": "2025/01/01", "position": 69, "query": "AI employment" }, { "date": "2025/02/01", "position": 82, "query": "AI employment" }, { "date": "2025/03/01", "position": 81, "query": "AI employment" }, { "date": "2025/05/01", "position": 81, "query": "AI employment" }, { "date": "2025/06/01", "position": 83, "query": "AI employment" } ]
Scale AI: Jobs | LinkedIn
Scale AI: Jobs
https://www.linkedin.com
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Jobs at Scale AI · Contributor Success Manager (CSM) · Contracts Manager · Recruiter, Public Sector · Technical Writer · Head of Public Sector Operations, ...
Sign in to see who you already know at Scale AI Sign in Welcome back Email or phone Password Show or By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy. New to LinkedIn? Join now or New to LinkedIn? Join now By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
2022-12-01T00:00:00
https://www.linkedin.com/company/scaleai/jobs
[ { "date": "2022/12/01", "position": 83, "query": "AI employment" }, { "date": "2023/02/01", "position": 81, "query": "AI employment" }, { "date": "2023/04/01", "position": 71, "query": "AI employment" }, { "date": "2023/05/01", "position": 73, "query": "AI employment" }, { "date": "2023/06/01", "position": 72, "query": "AI employment" }, { "date": "2023/08/01", "position": 70, "query": "AI employment" }, { "date": "2023/11/01", "position": 75, "query": "AI employment" }, { "date": "2023/12/01", "position": 73, "query": "AI employment" }, { "date": "2024/01/01", "position": 73, "query": "AI employment" }, { "date": "2024/02/01", "position": 85, "query": "AI employment" }, { "date": "2024/06/01", "position": 74, "query": "AI employment" }, { "date": "2024/07/01", "position": 72, "query": "AI employment" }, { "date": "2024/11/01", "position": 75, "query": "AI employment" }, { "date": "2025/01/01", "position": 73, "query": "AI employment" } ]
How AI Can Help Accelerate the Hiring Process - AEM
How AI Can Help Accelerate the Hiring Process
https://www.aem.org
[]
Sourcing, screening, and hiring employees can be a laborious, inefficient, and costly process. Some of today's proven artificial intelligence ( ...
By Gregg Wartgow, Special to AEM -- Sourcing, screening, and hiring employees can be a laborious, inefficient, and costly process. Some of today’s proven artificial intelligence (AI) tools can help, but they must be leveraged in the proper way. “Human resources should look at the recruitment and hiring process from the perspective of two audiences, the candidate and the hiring manager,” said Lindsey Kriete, Managing Director of Workforce Management at AEM member company LAK Group, which provides career coaching to professionals. Hiring managers want HR to serve up the best candidates as quickly as possible. Candidates want the process to be seamless and convenient. “When I look at the ideal end-to-end hiring process today, the priority is really around speed of hire, particularly with skilled trades such as welding,” said William Gott, Human Resources Manager at Wood-Mizer, a manufacturer of portable sawmill equipment. “It’s important to get candidates interested as quickly as possible.” Given the emphasis on speed, Gott believes AI has also become a priority. By integrating AI tools with the HR department’s ATS (applicant tracking system), several tasks at the front end of the workflow can be automated. Gott points to things like applicant screening, scheduling, consent to drug tests and background checks, and even interviewing. Even some of the tedious paperwork-related tasks with onboarding could be automated with the help of AI. Kriete and Gott shared their expertise on using AI to accelerate and enhance the hiring process during a AEM Member Education Webinar last month. Below are additional highlights from the webinar: Breaking up the Biggest Bottlenecks AI automation can help break up many of the bottlenecks that come into play with the traditional hiring workflow. But before that can happen, an HR department must ensure that its tech stack is assembled correctly. “Integrating the proper tools with your ATS can really make or break your funnel to recruit,” Gott said. “When you remove the things that take a lot of time, it improves speed. I would also argue that it helps improve quality because you can find qualified candidates faster. The best candidates will go toward the companies that respond the quickest because it feels like the companies are chasing them in some regard.” So, where are those workflow bottlenecks that AI can help break up? Job posting. Gott said he has retooled the entire hiring process over his five years at Wood-Mizer. Everything starts with the ATS and HRIS (human resources information system). Getting the right requisition form in, gaining approval, and getting a job posted as quickly as possible is essential today. AI automation greatly speeds up the process. “At the touch of a button, those job postings immediately go out to multiple locations, where we know we have success hiring people from,” Gott said. Applicant screening. Kriete said the perfect task that can be delegated to AI is the initial screening of applications. AI can filter out the unqualified candidates to remove much of the noise that makes things harder on the HR department. The sooner HR can present the hiring manager with a good list of qualified candidates, the better. Interview scheduling. According to Gott, one of the biggest bottlenecks is the infamous game of phone tag when attempting to schedule a candidate’s initial interview. As an alternative, AI allows companies to leverage automated text messaging, which Gott said is the preferred method of communication for most candidates today. Of course, automated emails could also be utilized. In either case, the candidate clicks on a link that takes them to a scheduling app to choose an available time slot that also works for them. In some cases, the initial interview itself can be conducted via automation Initial interview. Automated interviews can be effective, especially for production-type roles where numerous individuals are hired at once. Gott said an effective method is an on-demand phone or video interview tool that’s launched through a link that’s texted or emailed to the candidate. The questions are prerecorded by the company, and the candidate is able to complete the interview at a time that’s most convenient for them. “Additionally, AI transcribes the interview so I can watch it and/or read it at a time that works best for me,” Gott said. Writing interview questions. HR teams often have canned questions for evergreen positions. But for those more specialized roles, coming up with insightful questions to ask the candidate can be difficult—especially considering how busy the typical HR person is. “In many cases, I’ve found that good ole ChatGPT is awesome at recommending interview questions,” Kriete said. Making the offer and onboarding. Gott said his HR team continues to leverage AI long beyond the candidate’s initial interview. In fact, a candidate’s AI experience carries through the first three to six months of their employment. “The moment we’ve decided we want to hire someone, we’ve automated the offer, consent, and background,” Gott said. “We’ve also automated some of the onboarding and orientation. And once the employee has been on board with us, we’ve automated things like reviews and NPS (net promoter score) surveys so they feel like this process of automation is part of our culture. All of these tools are integrated with our HRIS and launch automatically.” Want to learn more? Participate in AEM’s open Workforce Development Committee Meetings to gain workforce insights and access to expert-led presentations. Striking the Right Balance As you can see, AI can play a valuable role throughout the hiring workflow, particularly at the front end. However, Kriete said it’s important to tread cautiously when it comes to some of the back-end processes, particularly when hiring more professional-type positions. Human interaction must continue to play an important role. “When you’re trying to hire someone, it’s important to convey the culture of the organization,” Kriete said. “There also needs to be some ability for hiring managers, supervisors, and candidates to simply get to know each other.” This illustrates an important concept. “AI is not separate from the human functions,” said Jeff Fitch, director of global dealer learning at Caterpillar and Chair of AEM’s Workforce Development Committee. “AI is integrated into the process to drive efficiencies so the human functions can be more productive.” Fitch moderated the June 25 webinar with Gott and Kriete. Chatbots are a shining example of where AI, when implemented incorrectly, can fail in comparison to genuine human interaction. “Chatbots can be great if the message is compelling and the text is sent to the right audience,” Kriete said. “At the same time, chatbots can be a huge turnoff if the message is long or doesn’t make sense, or is sent to the wrong person. The same can be said about any automated emails. It’s HR’s responsibility to set up their technology in a way that the messaging is clear, concise, and targeted.” Strengthen your workforce strategy by requesting information on best practices, tools, programs, and resources to help you attract and retain the right talent. Learn more. Gaining Confidence in the Tools By properly utilizing chatbots as described above, Gott said his HR team has gained tremendous efficiencies. The time it takes to hire assembly-type roles has been sliced in half. “It’s not uncommon to post the job, generate applications, and conduct phone interviews all on the first day,” Gott related. “Then we might conduct a physical interview with the top candidates the next day. We’ll often hire a qualified person within a week.” “If you would have told me a couple years ago that you could hire someone in a week, I would have said that was impossible,” Fitch remarked. “Now we’re starting to see that as a reality.” HR departments that are still new to AI shouldn’t be intimidated. Having the kind of success Gott and his team at Wood-Mizer have had will not happen overnight. But it can happen. “It takes commitment and a little upfront work, but you can get there,” Kriete said. “Once that upfront work is done, those automated processes are slick. There will always be hiccups, but the feedback I get from HR teams is that they love it.” To get started, Gott said HR professionals must commit to learning about the AI tools that are available. He likes a newsletter called Superhuman AI which covers the latest trends and innovations. He also suggests reaching out to some of the individual AI tool providers. Many are still startups, and will often allow companies to test their tool before going all in. Now’s the time to start testing, because ultimately going all in can greatly accelerate and improve your hiring process. About AEM Member Education Webinars AEM members have exclusive access to help them stay on top of emerging issues and trends via member education webinars. Experts break down industry issues and pinpoint critical changes in the landscape to help attendees refine their company’s strategy. For more information on the upcoming series of member education webinars, contact your Account Success Advisor.
2022-12-01T00:00:00
https://www.aem.org/news/how-ai-can-help-accelerate-the-hiring-process
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Meta Careers | Do the Most Meaningful Work of Your Career | Meta ...
Meta Careers | Do the Most Meaningful Work of Your Career
https://www.metacareers.com
[]
Join us to build the future of human connection and the technology that makes it possible. View jobs. Search Meta Careers.
ARTIFICIAL INTELLIGENCE Meta is all in on building the future of AI with Llama, our open-source collection of models. Llama turns inspiration into reality by translating and generating dialogue and code, solving complex problems, following instructions and more. See how a role in AI at Meta can help you drive the future of education, healthcare, finance, cybersecurity and more.
2022-12-01T00:00:00
https://www.metacareers.com/
[ { "date": "2022/12/01", "position": 87, "query": "AI employment" }, { "date": "2023/02/01", "position": 78, "query": "AI employment" }, { "date": "2023/04/01", "position": 72, "query": "AI employment" }, { "date": "2023/05/01", "position": 85, "query": "AI employment" }, { "date": "2023/06/01", "position": 71, "query": "AI employment" }, { "date": "2023/08/01", "position": 72, "query": "AI employment" }, { "date": "2023/11/01", "position": 82, "query": "AI employment" }, { "date": "2023/12/01", "position": 80, "query": "AI employment" }, { "date": "2024/01/01", "position": 77, "query": "AI employment" }, { "date": "2024/02/01", "position": 99, "query": "AI employment" }, { "date": "2024/06/01", "position": 72, "query": "AI employment" }, { "date": "2024/07/01", "position": 82, "query": "AI employment" }, { "date": "2024/11/01", "position": 76, "query": "AI employment" }, { "date": "2025/01/01", "position": 70, "query": "AI employment" }, { "date": "2025/02/01", "position": 86, "query": "AI employment" }, { "date": "2025/03/01", "position": 84, "query": "AI employment" }, { "date": "2025/05/01", "position": 84, "query": "AI employment" }, { "date": "2025/06/01", "position": 81, "query": "AI employment" } ]
AI & Robotics | Tesla
AI & Robotics
https://www.tesla.com
[]
We're hiring deep learning, computer vision, motion planning, controls, mechanical and general software engineers to solve some of our hardest engineering ...
Tesla participates in the E-Verify Program. Tesla is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to any factor, including veteran status and disability status, protected by applicable federal, state or local laws. Tesla is also committed to working with and providing reasonable accommodations to individuals with disabilities. Let your recruiter know if you need an accommodation at any point during the interview process. For quick access to screen reading technology compatible with this site, download a free compatible screen reader (view the free step-by-step tutorial). Contact [email protected] for additional information or to request accommodations.
2022-12-01T00:00:00
https://www.tesla.com/AI
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AI jobs are not the tech jobs you know - Technical.ly
AI jobs are not the tech jobs you know
https://technical.ly
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What do data centers, nuclear plants and coders have in common? Welcome to the generative artificial intelligence workforce.
This is a guest post by Stephen Babcock, the founder of Intake Media , where he embeds with early-stage entrepreneurs to create messaging and content that supports sales and fundraising. Babcock previously served as a journalist at a range of print and digital publications, including Technical.ly. It’s not just you. The messages we’re being delivered these days about AI are conflicted. The real impact is taking longer than expected. It’s already here. It’s hype. You can’t ignore it. It’s going to take jobs away. It’s going to create more jobs than we’ve ever seen. When history is written, this may all work itself out into one cohesive narrative. But right now, those of us trying to make sense of the change are left turning over every stone for signs of the truth. As a longtime media obsessive and even-longer-time word lover, I believe that subtle shifts in headlines can say a lot. Two recent ones particularly stood out to me. Both were about Amazon, but to this observer, they carry a global point. “Amazon to make massive $20B+ investment in Pennsylvania AI jobs — with data centers in tow,” Technical.ly wrote on June 9. Governor Josh Shapiro announces Amazon’s $20B investment in Pennsylvania (Courtesy) Big dollars! But for me, it was the phrase “AI jobs” that jumped out. As a former Technical.ly editor, I have plenty of firsthand evidence that a Technical.ly article typically talks about tech jobs, so the use of “AI jobs” is a significant shift. But more to the point, what is an AI job? Read the article — you should always read the article — and it’s clear that the word choice in the headline was prescient. These AI jobs are much different than “tech jobs” as we’ve conceived them over the last decade. In Amazon’s Pennsylvania investment, AI jobs will be tasked with operating nuclear power plants and building data centers. This is “the backbone for America’s AI infrastructure,” according to an AWS executive, and it’s kickstarting a massive investment in workforce development. That spine will need innovation to power its brain, but this is clearly a departure from the last two decades of tech. Instead of focusing on software and connected devices that promised to vault us into a new generation of boundaryless knowledge work, AI is harkening back to a more broad-shouldered category of industry that was once synonymous with Pennsylvania. Complex models require massive computational capacity to process data, which in turn requires lots and lots of energy. So we have to build more physical infrastructure to deliver it, operate those plants and figure out how to make them more productive. The former steel mill site in Bucks County that will house one data center may have simply been chosen because the space was available, but it’s dripping with symbolism nonetheless. Coal delivered the massive energy gains we needed for the industrial revolution, just as nuclear power promises to do in the age of AI. Plentiful steel helped us create marvels of engineering that reshaped how we moved and organized ourselves, just as data pledges to do for AI today. There was good-paying work in all of it during the 20th century, just as Amazon’s announcement promises for the 21st. The 100-year arcs may write themselves. But in the more immediate timeline of years and decades, it’s worth thinking about the shift that this is bringing to the landscape of technology and careers today. That brings us to a second headline about jobs and Amazon in recent weeks, where the New York Times wrote that “Some Coders Say Their Jobs Have Begun to Resemble Warehouse Work.” It was doubtless lost on the editor that Amazon redefined warehouse work for the Internet generation with its fulfillment centers, where humans and robots worked side-by-side to collapse the time between click and delivery. Over the last decade, we also saw how Amazon shaped local economies. Throughout post-industrial cities, the appearance of a fulfillment center provided both a brand name and an instant job creator, checking off a couple of boxes on the wishlist of an economic development professional. Now it is the coders who hold tech jobs that are doing something like warehouse work, but they won’t be in next-generation warehouses. After all, the coders were never in fulfillment centers. They were largely in Seattle, and then more came to DC metro, and then we learned they were distributed in a few other locales, as well. As Amazon’s pre-pandemic HQ2 competition showed, attracting tech jobs required a vastly different playbook that was very much of its time. HQ2 became a litmus test for how the leaders of midsize cities from the Rust Belt to the Sun Belt to the South assembled the pieces of an innovation ecosystem that would attract and retain software developers for years into the future — and the land to accommodate a massive new mixed-use property. Most had some combination of university and corporate anchors to grow tech talent, investors and incubators to seed startups, and tax and quality-of-living policy changes to improve the city’s brand among millennials in the sought-after developer cohort. Metropolitan Park, part of Amazon’s HQ2 development, in 2023. (Lucas Jackson/Amazon) The tech push produced new companies and reinvigorated urban life, but we’ll not soon forget how the era was equally characterized by a supernova of a software engineering job market that eventually crashed into some balance of inflation and automation. Last month’s announcement in Pennsylvania has a flavor of “America’s Next Top Model”-style competition, as Amazon held out the promise that it may bring data centers to additional communities. But HQ2 it is not. In fact, if Amazon were to launch a bid for HQ3 today, the ingredients would likely be different. The company’s announcement in Pennsylvania still states universities and innovation hubs are needed, but in quotations supporting the initiative, politicians also cite water and construction, working families and clean energy. Success may yet again be measured in wattage and square footage, not app downloads. Tech is about where we’re heading, and the shift to AI jobs is underway. It will reshape where engineers and construction workers seek work, how they build careers, where they move their families, and what motivates them. They will work on AI and use AI to get the job done. This all may or may not be inevitable. But somewhere between tech giants and local leaders, steel mills and headlines, the signs of change are there. How will you read them?
2025-07-07T00:00:00
2025/07/07
https://technical.ly/professional-development/future-ai-jobs-amazon-guest-post/
[ { "date": "2022/12/01", "position": 94, "query": "AI employment" } ]
Red Hat Jobs | Opportunities are open
Opportunities are open
https://www.redhat.com
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Red Hat is an open hybrid cloud technology leader, delivering a consistent, comprehensive foundation for transformative IT and artificial intelligence (AI) ...
Culture Who we are We’re a leader in open source because of our open and inclusive environment. Red Hatters are encouraged to bring their best ideas, no matter their title or tenure. Our collaborative, inclusive spirit is what makes us Red Hat. We’ve been committed to working openly together for more than 25 years.
2022-12-01T00:00:00
https://www.redhat.com/en/jobs
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Remote Jobs - Zoom Careers
Search Page
https://careers.zoom.us
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AI Software Engineer. R15882. Seattle, Washington, United States. Engineering (EN). Zoom. AI Software Engineer What you can expect As an AI ...
R16882 Remote Remote, United States Marketing (MK) Zoom What you can expect Zoom is more than just meetings—we’re shaping how people connect, collaborate, and get work done across the globe. We're looking for a strategic, insight-driven leader to build and lead our Future of Work Insights & Content fun...
2022-12-01T00:00:00
https://careers.zoom.us/jobs/search
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Search Jobs — Google Careers
Search Jobs — Google Careers
https://www.google.com
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Machine Learning Engineer, Search Ads, Shopping Relevance Models · Machine Learning Engineer, Personal AI, Google Pixel · Machine Learning Algorithm Engineer, ...
Equal Opportunity Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.
2022-12-01T00:00:00
https://www.google.com/about/careers/applications/jobs/results?q=machine+learning
[ { "date": "2022/12/01", "position": 97, "query": "AI employment" }, { "date": "2023/02/01", "position": 88, "query": "AI employment" }, { "date": "2023/04/01", "position": 83, "query": "AI employment" }, { "date": "2023/05/01", "position": 87, "query": "AI employment" }, { "date": "2023/06/01", "position": 87, "query": "AI employment" }, { "date": "2023/08/01", "position": 86, "query": "AI employment" }, { "date": "2023/11/01", "position": 88, "query": "AI employment" }, { "date": "2023/12/01", "position": 87, "query": "AI employment" }, { "date": "2024/01/01", "position": 90, "query": "AI employment" }, { "date": "2024/02/16", "position": 90, "query": "AI hiring" }, { "date": "2024/06/01", "position": 89, "query": "AI employment" }, { "date": "2024/07/01", "position": 89, "query": "AI employment" }, { "date": "2024/11/01", "position": 89, "query": "AI employment" }, { "date": "2025/01/01", "position": 89, "query": "AI employment" }, { "date": "2025/02/01", "position": 81, "query": "AI employment" }, { "date": "2025/03/01", "position": 79, "query": "AI employment" }, { "date": "2025/05/01", "position": 97, "query": "AI employment" }, { "date": "2025/06/01", "position": 82, "query": "AI employment" } ]
Explore Career and Job Opportunities - Intuit
Explore Career and Job Opportunities
https://www.intuit.com
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Build an AI-driven expert platform and help solve customers' biggest financial challenges ... We make employment decisions without regards to race, color ...
Intuit is proud to be an equal opportunity employer. We make employment decisions without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability status, pregnancy, or any other basis protected by federal, state or local law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please talk with your recruiter or send a request to [email protected] .
2022-12-01T00:00:00
https://www.intuit.com/careers/
[ { "date": "2022/12/01", "position": 99, "query": "AI employment" }, { "date": "2023/02/01", "position": 90, "query": "AI employment" }, { "date": "2023/04/01", "position": 91, "query": "AI employment" }, { "date": "2023/05/01", "position": 92, "query": "AI employment" }, { "date": "2023/06/01", "position": 91, "query": "AI employment" }, { "date": "2023/08/01", "position": 88, "query": "AI employment" }, { "date": "2023/11/01", "position": 92, "query": "AI employment" }, { "date": "2023/12/01", "position": 93, "query": "AI employment" }, { "date": "2024/01/01", "position": 94, "query": "AI employment" }, { "date": "2024/06/01", "position": 93, "query": "AI employment" }, { "date": "2024/07/01", "position": 92, "query": "AI employment" }, { "date": "2024/11/01", "position": 93, "query": "AI employment" }, { "date": "2025/01/01", "position": 92, "query": "AI employment" }, { "date": "2025/02/01", "position": 93, "query": "AI employment" }, { "date": "2025/03/01", "position": 91, "query": "AI employment" }, { "date": "2025/05/01", "position": 91, "query": "AI employment" }, { "date": "2025/06/01", "position": 89, "query": "AI employment" } ]
AI Paygrades
AI Paygrades
https://aipaygrad.es
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Statistics of industry job offers in Artificial Intelligence (AI) ; Median overall · 326,613 ; Base salary · 160,000 ; Equity grant · 103,750 ; Target bonus · 20,250 ...
Statistics of industry job offers in Artificial Intelligence (AI) Contribute your (past or recent) offer(s), and spread the word. Need help negotiating? Here's a word from .
2022-12-01T00:00:00
https://aipaygrad.es/
[ { "date": "2022/12/01", "position": 2, "query": "AI wages" }, { "date": "2023/01/01", "position": 2, "query": "AI wages" }, { "date": "2023/02/01", "position": 3, "query": "artificial intelligence wages" }, { "date": "2023/04/01", "position": 2, "query": "AI wages" }, { "date": "2023/05/01", "position": 2, "query": "AI wages" }, { "date": "2023/05/01", "position": 4, "query": "artificial intelligence wages" }, { "date": "2023/06/01", "position": 2, "query": "AI wages" }, { "date": "2023/07/01", "position": 3, "query": "artificial intelligence wages" }, { "date": "2023/08/01", "position": 2, "query": "AI wages" }, { "date": "2023/08/01", "position": 3, "query": "artificial intelligence wages" }, { "date": "2023/09/01", "position": 4, "query": "artificial intelligence wages" }, { "date": "2023/10/01", "position": 2, "query": "AI wages" }, { "date": "2023/12/01", "position": 4, "query": "artificial intelligence wages" }, { "date": "2024/01/01", "position": 2, "query": "AI wages" }, { "date": "2024/01/01", "position": 3, "query": "artificial intelligence wages" }, { "date": "2024/02/01", "position": 3, "query": "artificial intelligence wages" }, { "date": "2024/03/01", "position": 2, "query": "AI wages" }, { "date": "2024/03/01", "position": 3, "query": "artificial intelligence wages" }, { "date": "2024/04/01", "position": 3, "query": "artificial intelligence wages" }, { "date": "2024/05/01", "position": 2, "query": "AI wages" }, { "date": "2024/07/01", "position": 2, "query": "AI wages" }, { "date": "2024/08/01", "position": 3, "query": "artificial intelligence wages" }, { "date": "2024/09/01", "position": 2, "query": "AI wages" }, { "date": "2024/12/01", "position": 2, "query": "AI wages" }, { "date": "2025/01/01", "position": 2, "query": "AI wages" }, { "date": "2025/02/01", "position": 3, "query": "artificial intelligence wages" }, { "date": "2025/03/01", "position": 2, "query": "AI wages" }, { "date": "2025/03/01", "position": 3, "query": "artificial intelligence wages" }, { "date": "2025/04/01", "position": 2, "query": "AI wages" }, { "date": "2025/04/01", "position": 19, "query": "artificial intelligence wages" }, { "date": "2025/06/01", "position": 2, "query": "AI wages" }, { "date": "2025/06/01", "position": 3, "query": "artificial intelligence wages" } ]
Top 10 Highest Paying Artificial Intelligence Jobs & Best Salaries 2025
Top 10 Highest Paying Artificial Intelligence (AI) Jobs 2025
https://www.nexford.edu
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Top 10 Highest Paying Artificial Intelligence Jobs & Best Salaries 2025 · 1. Machine Learning Engineer · 2. AI Engineer · 3. Data Scientist · 4.
Top 10 Highest Paying Artificial Intelligence Jobs & Best Salaries 2025 1. Machine Learning Engineer A machine learning engineer has experience in machine learning and creates machine learning algorithms and models that can analyze large datasets to make predictions. Machine learning jobs involve the designing, creating, and developing and implementing machine learning models are the mix of tasks that most machine learning engineers will be asked to undertake. To create and implement sophisticated algorithms and systems, machine learning engineers collaborate closely with software engineers and data scientists. The average annual salary of a machine learning engineer in the US is $​​109,143. 2. AI Engineer AI engineers play a crucial role in developing and implementing artificial intelligence (AI) systems. Their responsibilities include, developing AI models and algorithms, building AI systems, optimizing AI performance, data preprocessing and cleaning, collaborating with data scientists and software engineers, and finally, staying on top of AI advancements. To become an AI engineer, you need a combination of technical skills, knowledge in mathematics and statistics, and proficiency in programming languages. The average annual salary of an AI engineer in the US is $160,757. 3. Data Scientist Data scientists, or big data engineers, obviously have experience in data science, and employ statistical and machine learning techniques to analyze huge data sets, learn from data, and uses machine learning algorithms to glean insights from that unstructured data. To find trends and patterns in data, they collaborate closely with business executives before using this knowledge to make data-driven decisions. The average annual salary of a data scientist in the US is $65,674. Are you ready to take your career to the next level? Nexford's Career Path Planner takes into account your experience and interests to provide you with a customized roadmap to success. Receive personalized advice on the skills and qualifications you need to get ahead in areas like finance, marketing, management and entrepreneurship. Take the quiz to get started now! 4. Computer Vision Engineer To help computers comprehend and interpret visual data, computer vision engineers combine ai-powered machine learning and computer vision approaches. To create systems that can detect and categorize photographs, movies, and other visual data, they collaborate closely with other engineers. Computer Vision Engineers are one of the highest paying jobs in AI. The average annual salary of a computer vision engineer in the US is $168,803. 5. Natural Language Processing Engineer Natural language processing engineers specialize in natural language processing (NLP) and employ tools and platforms, like speech recognition, to employ machine learning and NLP methods to help computers comprehend and interpret human discourse. In their engineer positions, NLP engineers can take unstructured speech and text and turn it into something that a computer can understand. They collaborate closely with other engineers to create systems that can comprehend human voice and text and react accordingly. The average annual salary of a computer vision engineer in the US is $86,193. 6. Deep Learning Engineer There are a number of exciting jobs in the AI field and one such vocation is a deep learning engineer. Deep learning engineers utilize various methods to give computers algorithms that enable computers with the ability to learn from massive amounts of data. To develop and execute sophisticated neural networks and other deep learning algorithms, deep learning engineers collaborate closely with data scientists and other technologists. The average annual salary of a deep learning engineer in the US is $141,435. 7. AI Research Scientist An AI Research Scientist asks new and creative questions that can be answered by AI. They work on cutting-edge research projects and develop new AI technologies that businesses can use to improve their processes. It is the job of an AI Research Scientist to push the boundaries of what is possible with AI. Before a company invests millions into developing a new tool or product, it is the research scientists who prove their viability. Demand for artificial intelligence research scientists are ever increasing. The average annual salary of an AI research scientist in the US is $115,443. 8. Business Development Manager Of all of the jobs in artificial intelligence, the AI Business development managers are some of the highest paid salary in 2024 and they are generally in charge of finding new business possibilities and formulating plans for expanding the company. In order to locate new markets and create alliances, they collaborate closely with other managers and executives. The average annual salary of an AI business development manager in the US is $196,491. 9. AI Product Manager AI Product Manager jobs pay well because the person is expected to lead and guide a team to build an AI-based solution. To find new opportunities and establish strategies for developing new AI products, they collaborate closely with engineers and data scientists. An AI Product Manager has expertise in deep learning and machine learning, and knows how AI techniques can be used to solve any given problem. They will be able to determine exactly how an existing product can be improved by using machine learning. The average annual salary of an AI product manager in the US is $128,091. 10. AI Consultant An AI consultant advises businesses on how AI and machine learning can be applied into their operations to improve efficiency, reduce costs and increase revenue. They collaborate closely with engineers and other consultants to assist clients in identifying new opportunities and formulating plans for utilizing AI to enhance business operations. It is one of the higher salary brackets in AI. The average annual salary of an AI consultant in the US is $124,843. Conclusion If you are looking to get in to or break in to the AI industry and forge a career in the field of AI, but lack the necessary skills to build a long and lucrative career, an online MBA with Specialization in Advanced AI and Automation from Nexford University could well be the best place to start. You’ll need to complete three specialized courses in addition to 10 core MBA courses. You’ll learn skills based on the latest employer needs and market trends – this is what we call our Workplace Alignment Model – our curriculum is designed to equip you with the skills you need and employers are looking for. Looking to expand your skillset and get a high-paying career in AI? Discover how you can acquire the most in-demand skills with our free report, and open the doors to a successful career in artificial intelligence. Download the free report today! Want to take your career even further? Consider how an online BBA with specialization in AI or an online MBA with specialization in advanced AI can help you develop these skills and increase your earning potential. FAQs What skills are required to get a high paying job in AI? A background in programming languages like Python, Java, C/C++, and experience in artificial intelligence, machine learning, or natural language processing are some of the top skills employers look for in AI applicants. The top 5 skills to get a high paying job in AI include, Programming, Database Modelling, Data Warehousing and Data Processing, Machine Learning, knowledge of Intelligent User interfaces, and Problem Solving. Do I need to have a degree to work in AI? Expect most jobs in AI to require a bachelor's degree or higher. A bachelor's degree in computer science is essential for any employment in AI. Many companies and enterprises prefer a Master's or higher degree in computer science for the same position. A solid portfolio or prior programming skills might serve as an alternative to a master's degree. Are there any high paying entry-level careers in AI? As the AI industry is just exploding right now, it stands to reason that there will be a load of jobs, and especially entry level jobs to pick from. If you are just getting started in AI you should consider getting started as an Automation Technician, Operations Analyst, Automation Software Engineer, Mechatronic Engineer, and ai developers. What is the average salary of an AI professional and what factors affect this? The national average salary for a Artificial Intelligence is $104,951. Specific skills, location, industry and educational background are also factors that can affect your pay bracket. One of the biggest factors however that can influence your salary is your level of experience. It makes sense - the more experience you have working as an AI professional, the better off you will be. The more expertise you have, the more you can expect to earn. How can I find high-paying AI jobs? As per any other industry, there are several online job boards that you can use to hunt for the latest and greatest AI jobs across the globe. Glassdoor is one of the biggest, but other top job boards include, Indeed, LinkedIn, Reed, AI Job, Technojobs, and Totaljobs. These are all worthwhile visiting on a regular basis as we all know that artificial intelligence is one of the highest paying industries right now. Are you ready to take your career to the next level? Nexford's Career Path Planner takes into account your experience and interests to provide you with a customized roadmap to success. Receive personalized advice on the skills and qualifications you need to get ahead in areas like finance, marketing, management and entrepreneurship. Take the quiz to get started now! How can I increase my chances of landing a high-paying career in AI? AI technology offers some of the highest-paying and most in-demand careers around. Some have the predetermined skills to succeed, others have attended courses online, whilst many have found that attending intensive bootcamps can help them to get a foot in the door, but popular opinion dictates that if you want to get into the AI field, jump-start your career in it, and do ai right, you should join the technological revolution and use reinforcement learning to get a master's degree in computer science or a related field such as data analytics. How can I prepare for an AI job interview? As with any other job interview it would be well advised to research the company and the person interviewing you, know the job description and how your skills can feed into that, and also research some intelligent and relevant questions that you can ask the interviewer. Either way, you'll need to know what to expect going into an AI interview. Here are five interview tips for speaking to AI, according to experts. One, treat it like a normal job interview, two, practice your non-verbal cues, three, remember the time limit, four, don't forget the purpose of the interview and answer accordingly. Want to land that dream job in AI? Consider how our online MBA with Specialization in Advanced AI can help acquire the necessary skills and through the skills you learn, increase your earning potential by showing you the skills to become an effective manager and AI professional.
2022-12-01T00:00:00
https://www.nexford.edu/insights/highest-paying-ai-jobs
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ML / AI Software Engineer Salary - Levels.fyi
AI Software Engineer Salary
https://www.levels.fyi
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The median ML / AI Software Engineer Salary is $245102. View ML / AI Software Engineer salaries across top companies broken down by base, stock, and bonus.
Poll Is it just me, or is the tech job market completely silent lately? Hi all — just wondering if anyone else is facing the same thing. Been applying to roles lately (tech, backend-focused), and it’s been radio silence. No responses, no interviews, not even rejections. It almost feels like applications are vanishing into a black hole. I know the marke...
2022-12-01T00:00:00
https://www.levels.fyi/t/software-engineer/focus/ml-ai
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AI Salaries in the US [For Different Roles] [2025] - DigitalDefynd
AI Salaries in the US [For Different Roles] [2025]
https://digitaldefynd.com
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Salary Highlight: In the US, the salary for an AI Product Manager typically ranges from $110,000 to $160,000 annually, depending on the complexity of the AI ...
Artificial Intelligence (AI) has emerged as a foundational element of innovation across various industries, fundamentally transforming our interactions with technology and data. This revolution influences everything from daily operations to strategic decision-making. As AI continues to grow, so does the job opportunities it offers. This blog delves into the diverse roles within the AI sector, highlighting the varying salaries these positions command in the United States. By examining these roles, we aim to provide valuable insights for professionals navigating the AI job market, whether they are just starting their careers or looking to advance. Here, you will find an analysis of salary ranges across multiple AI designations, providing a clear picture of what to expect financially from a career in this dynamic field. AI Salaries in the US [For Different Roles] [2025] Role Starting Salary Average Salary Top Salary Role Description AI Research Scientist $90,000 $125,000 $160,000+ Focuses on developing new AI methodologies and advancing the understanding of existing AI technologies. Machine Learning Engineer $100,000 $140,000 $180,000+ Builds and manages AI models to enable machines to learn from data without explicit programming. Data Scientist $95,000 $122,500 $150,000+ Analyzes large data sets to extract actionable insights and build predictive models. AI Software Developer $85,000 $107,500 $130,000+ Develops the software that integrates AI technologies into usable applications and systems. Robotics Engineer $80,000 $110,000 $140,000+ Designs and builds robots that perform tasks in various industrial, commercial, or personal settings. NLP Engineer $100,000 $125,000 $150,000+ Specializes in programming computers to process and analyze large amounts of natural language data. Computer Vision Engineer $90,000 $115,000 $140,000+ Develops AI systems that can process and interpret visual information from the world around us. AI Product Manager $110,000 $135,000 $160,000+ Manages the development and strategy of AI products, bridging technical teams and business objectives. AI Ethics Officer $95,000 $115,000 $135,000+ Ensures AI technologies are developed and deployed in a responsible and ethical manner. AI Systems Architect $120,000 $145,000 $170,000+ Designs the overall structure of AI systems, ensuring they are robust, scalable, and integrate smoothly with existing infrastructures. Chief AI Officer (CAIO) $180,000 $215,000 $250,000+ Oversees all AI initiatives across a company, aligning AI strategies with business goals. AI Operations Manager $90,000 $115,000 $140,000+ Manages the day-to-day operations and maintenance of AI systems within an organization. Related: How to negotiate a high AI engineer salary? Overview of AI Salaries in the US In the fast-evolving field of Artificial Intelligence, salary structures are highly diverse, reflecting the wide range of technologies and applications from which they originate. This diversity in compensation mirrors the broad spectrum of expertise and roles within the AI industry. Across the United States, AI professionals enjoy competitive pay, reflecting the high demand and specialized skills required in this sector. Wages vary greatly based on geographic zone, industry, and individual background. For example, AI positions in tech-centric cities such as San Francisco and New York typically offer higher salaries, which can be attributed to the higher cost of living and the dense concentration of technology firms in these areas. This geographic salary variation underscores the impact of local economic factors on compensation within the tech industry. Additionally, professionals with advanced machine learning, data science, and robotics skills are positioned at the higher end of the salary spectrum. This section will explore these variations, providing a broad understanding of what AI professionals can expect to earn in different scenarios. Specific AI Roles and Their Salaries AI Research Scientist AI Research Scientists lead the charge in advancing artificial intelligence, concentrating on devising new methods and deepening understanding of how AI algorithms can tackle complex challenges. This role typically involves a high level of theoretical knowledge and the practical ability to implement algorithms that can learn and adapt. AI Research Scientists require an in-depth understanding of machine learning, statistics, and programming. They typically hold advanced degrees in computer science, mathematics, or similar fields. Their primary duties involve designing and testing AI models, publishing their research, and working with engineering teams to incorporate successful algorithms into broader projects and products. The career prospects for AI Research Scientists are excellent, with opportunities to work in technology, healthcare, finance, and automotive sectors. These professionals are critical in driving innovation and maintaining competitive edges, making them highly valued in the job market. As AI evolves, the role of the AI Research Scientist will remain crucial in discovering new potentials and applications of artificial intelligence. Salary Highlight: In the United States, the average salary for an AI Research Scientist ranges from $90,000 for entry-level positions to over $160,000 for experienced individuals in specialized industries or leading tech hubs. Machine Learning Engineer Machine Learning Engineers are vital in the AI industry, creating data-driven algorithms that enable machines to learn and function independently without direct programming. Their work, which merges data science with software engineering, involves building and managing platforms that process complex data sets and generate predictive models. These experts are highly experienced in utilizing machine learning frameworks and libraries such as TensorFlow and PyTorch. They often have a strong background in data science, statistics, and programming, with a keen ability to translate theoretical models into practical applications. Machine Learning Engineers work closely with AI researchers to optimize algorithms and are instrumental in bringing AI products from concept to deployment. The demand for Machine Learning Engineers has skyrocketed as businesses across various sectors seek to harness the predictive power of AI. They find possibilities in tech giants, startups, and enterprises like finance and healthcare, which rapidly incorporate AI solutions for improved decision-making. Machine Learning Engineers innovate and ensure that the solutions are scalable and sustainable within the company’s infrastructure. This role is crucial for companies leveraging AI for long-term strategic gains. Salary Highlight: Salaries for Machine Learning Engineers in the US start at around $100,000 annually and can exceed $180,000 for those with substantial experience or working in competitive markets like Silicon Valley. Related: Top Countries to build a career in AI Data Scientist Data Scientists play a pivotal role in extracting meaningful insights from large volumes of data, utilizing both statistical analysis and machine learning techniques. This position bridges the gap between data analysis and practical application, ensuring that data-driven decisions can be made efficiently and accurately. Specialists in this position generally excel in statistical research, predictive modeling, and data visualization. They are adept at using tools like Python, R, SQL, and SAS to mine data, predict trends, and interpret complex data sets into actionable insights. Data Scientists frequently team closely with industry stakeholders to comprehend their requirements and deliver data that informs strategic decisions. The scope of a Data Scientist’s work can vary widely across different industries, including tech, healthcare, finance, and retail, making it a versatile and in-demand career choice. They are essential in helping organizations optimize operations, identify new market opportunities, and influence product development with data-backed strategies. As the demand for advanced data analysis and modeling continues to grow, the role of the Data Scientist becomes increasingly important in helping businesses stay competitive in a data-driven world. Salary Highlight: In the US, Data Scientists earn an average starting salary of about $95,000, which can rise to over $150,000 with experience and specialization, especially in high-demand areas or industries. AI Software Developer AI Software Developers are essential to structuring and maintaining the software systems that underpin AI applications. They specialize in writing robust code that integrates AI models into functional software products, making AI accessible and usable across various platforms. This position needs a deep learning of both software development techniques and AI technologies. Professionals must expertly navigate these areas to excel in their functions. AI Software Developers must be proficient in programming languages like Python, Java, and C++ and have a strong grasp of AI frameworks such as TensorFlow or Keras. They are critical in developing AI-driven applications like virtual assistants, automated customer support systems, and personalized recommendation engines. Their work often involves operating closely with Machine Learning Engineers and Data Scientists to confirm that AI models are optimally incorporated into software solutions. AI Software Developers are increasingly sought after in diverse industries such as technology, finance, healthcare, and entertainment. Their expertise drives innovation and enhances operational efficiency within these fields. The ability to translate complex AI concepts into user-friendly software makes AI Software Developers key players in any tech-driven company. They contribute to the development of innovative products and enhance existing applications with AI capabilities to improve performance and user engagement. Salary Highlight: The salary for AI Software Developers in the US typically starts around $85,000 annually but can go well beyond $130,000 for those with extensive experience or in senior roles at major firms. Robotics Engineer Robotics Engineers are pivotal in designing and building machines increasingly integral to various industries, from manufacturing to healthcare. These professionals combine computer science, mechanical engineering, and electrical engineering knowledge to create robots that can perform tasks traditionally done by humans. The role of a Robotics Engineer involves extensive programming and system design, focusing on making efficient and safe robots. They collaborate with sensors, actuators, and software to equip robots to process information and engage with their surroundings. This requires a solid understanding of AI, particularly in machine learning and computer vision, to empower robots with autonomous decision-making capabilities. Robotics Engineers are in demand across several sectors, including automotive, aerospace, electronics manufacturing, and entertainment. Their work improves productivity and security and pushes the boundaries of what machines can gain, contributing to technological improvements and quality of life. As robotics continues to expand, the role of Robotics Engineers becomes increasingly important, with opportunities for innovation in areas like robotic surgery and automated transportation. Salary Highlight: In the United States, the average salary for a Robotics Engineer starts at approximately $80,000 and can rise to around $140,000 or more, depending on expertise, industry, and geographic location. Natural Language Processing Engineer Natural Language Processing (NLP) Engineers specialize in enabling machines to understand and respond to human language, a cornerstone capability for many AI-driven applications like chatbots, translation services, and voice-activated assistants. These engineers leverage their knowledge in AI and linguistics to enable computers to process and analyze extensive natural language data. Their efforts focus on training machines to comprehend and accurately interpret human language. An NLP Engineer’s role involves developing algorithms to recognize speech patterns, understanding semantics, and generating human-like responses. This requires proficiency in AI, machine learning, deep learning, and syntax to effectively program systems that can understand and mimic human communication. NLP Engineers often work closely with AI researchers and data scientists to refine algorithms based on machine learning models, improving the accuracy and efficiency of language understanding. Their work is critical in industries such as technology, customer service, and healthcare, where the ability to interact naturally with users can significantly impact user experience and operational efficiency. With the increasing adoption of AI in consumer and business applications, NLP Engineers play a vital role in bridging human-computer interaction, making technological advancements more accessible and functional for everyday use. Salary Highlight: Salaries for NLP Engineers in the US typically range from $100,000 to $150,000 annually, reflecting the specialized skills and high demand for professionals in this niche field of AI. Related: Top cities in US to build a career in AI Computer Vision Engineer Computer Vision Engineers concentrate on helping machines to interpret and comprehend the visual world. Utilizing AI and machine learning, they design algorithms that authorize computers to process and analyze visual data from the environment, such as images and videos. This capability is vital for applications ranging from autonomous vehicles and facial recognition systems to augmented reality and quality control in manufacturing. The work of a Computer Vision Engineer involves creating advanced machine learning models to detect, categorize, and track objects, and to analyze visual content to make decisions. They need a robust understanding of neural networks, pattern recognition, and digital image processing. Typically, these engineers are skilled in programming languages like Python and C++ and often use frameworks such as OpenCV or TensorFlow. Computer Vision Engineers are crucial in tech industries, security, healthcare, and retail, where their expertise supports the development of products that rely heavily on visual inputs. Their ability to innovate in how machines perceive and interact with their surroundings is transforming numerous sectors. Salary Highlight: The salary for Computer Vision Engineers in the US generally starts around $90,000 but can exceed $140,000 for those with extensive experience or in specialized roles, highlighting the high demand and value placed on this expertise in the tech sector. AI Product Manager AI Product Managers are crucial in bridging the gap between technical AI teams and commercial product strategies. They manage the development and deployment of AI-powered products, making sure these innovations are in line with business objectives and fulfill market demands. Their oversight ensures that AI implementations enhance company strategies and effectively address consumer requirements. This role requires a deep knowledge of both AI technology and product management. AI Product Managers must be adept at translating technical details into benefits for users and stakeholders, and they manage the product lifecycle from concept through launch. They collaborate closely with engineers, data scientists, marketers, and sales groups to define product vision, prioritize features, and create go-to-market strategies. The responsibilities of an AI Product Manager include setting clear objectives for AI projects, managing timelines, and overseeing cross-functional teams to deliver high-quality products that are user-friendly and commercially viable. They also play a key role in customer engagement, gathering feedback to refine products and adapt to changing market demands. AI Product Managers are increasingly sought after in industries like technology, finance, healthcare, and retail, where AI enhances customer experiences and operational efficiencies. Salary Highlight: In the US, the salary for an AI Product Manager typically ranges from $110,000 to $160,000 annually, depending on the complexity of the AI applications involved and the individual’s experience in managing AI-driven projects. AI Ethics Officer AI Ethics Officers are increasingly vital as organizations seek to ensure their AI technologies are developed and deployed responsibly. This role involves addressing ethical considerations around AI, such as fairness, transparency, accountability, and the impact on privacy and civil liberties. AI Ethics Officers work to develop guidelines and frameworks that align AI practices with ethical standards and regulatory requirements. Professionals in this position collaborate closely with technologists, legal teams, and policymakers to assess AI projects for potential ethical risks, implement oversight mechanisms, and advocate for ethical decision-making throughout the AI lifecycle. They are tasked with educating and training AI teams on ethical practices and are often involved in public discussions to shape policies around AI use. The need for AI Ethics Officers spans multiple industries, including technology, healthcare, finance, and government. Their work is crucial in maintaining trust and credibility in AI applications by ensuring that these technologies are effective, fair, and just. Salary Highlight: The salary for AI Ethics Officers in the US generally starts around $95,000 but can go up to $135,000 or more, reflecting the specialized nature of the role and its importance in guiding the responsible development and use of AI technologies. Related: How to become an AI security specialist? AI Systems Architect AI Systems Architects are crucial for designing the overarching structures of AI systems, ensuring they are robust, scalable, and capable of integrating with existing technological infrastructures. This role involves a deep understanding of hardware and software components that make up AI solutions, making it possible to architect systems that effectively support AI applications. These professionals are responsible for the initial planning, design, testing, and implementation of complex AI systems. They work closely with AI developers, engineers, and business leaders to create blueprints that outline the integration of machine learning models and other AI functionalities into the business environment. AI Systems Architects also guarantee that the systems are secure and adhere to industry standards and regulations. Their expertise is essential in industries ranging from tech and finance to healthcare and manufacturing, where AI systems must be tailored to specific operational needs and strategic goals. AI Systems Architects play a key role in making AI initiatives successful by aligning technological capabilities with business objectives. Salary Highlight: In the US, salaries for AI Systems Architects typically range from $120,000 to over $170,000 annually. This range reflects their critical role in deploying AI technologies and the high expertise required to design sophisticated AI systems. Chief AI Officer The Chief AI Officer (CAIO) is a senior executive who oversees the strategic integration of artificial intelligence across a company’s operations and products. This leadership position sets the AI vision, aligns AI initiatives with business goals, and ensures that AI technologies drive innovation and competitive advantage. CIOs serve as essential connectors between technical AI teams and the executive board, effectively communicating the benefits and implications of AI strategies to stakeholders across the organization. This role ensures that all company levels understand and help AI initiatives. They supervise the development and enactment of AI policies, manage AI talent, and ensure that AI projects stick to ethical standards and regulatory compliance. Institutions increasingly depend on AI to improve decision-making and operating efficiency, so the CAIO is essential in finance, healthcare, retail, and technology. Their expertise crucially shapes the company’s strategic direction, utilizing AI to tackle complex business challenges and seize new opportunities. This allows the institution to innovate constantly and sustain a competitive edge in its industry. Salary Highlight: Reflecting the high responsibility and impact of this role, the salary for a Chief AI Officer in the US can range from $180,000 to well over $250,000 annually, depending on the size of the company, the industry, and the geographic location. This compensation underscores the CAIO’s significant influence and strategic importance in guiding successful AI adoption and integration within leading firms. AI Operations Manager AI Operations Managers are critical in ensuring the smooth operation and scalability of AI systems within an organization. This managerial position focuses on the practical aspects of deploying and maintaining AI solutions, optimizing performance, and ensuring that these systems meet business requirements efficiently. Responsibilities of an AI Operations Manager include overseeing the infrastructure that supports AI applications, managing AI deployment schedules, and coordinating between cross-functional teams to resolve technical issues. They ensure that AI tools and systems are up-to-date and function correctly and implement processes that maintain the integrity and security of data used by AI models. AI Operations Managers are key in industries that rely heavily on AI for day-to-day operations, such as e-commerce, telecommunications, and digital services. Their ability to manage and optimize AI operations directly impacts a company’s ability to innovate and maintain competitive advantages. By continuously monitoring system performance and facilitating rapid responses to operational challenges, AI Operations Managers ensure that AI applications deliver consistent value and effectively support business goals. Salary Highlight: In the United States, the salary for an AI Operations Manager typically ranges from $90,000 to $140,000 annually. This range reflects their essential role in maintaining AI technologies’ operational efficiency and effectiveness across various sectors. Related: How to prevent AI hallucinations? Conclusion As explored in this blog, salaries for AI roles in the US differ significantly, influenced by factors like experience, location, and specialization. These variations reflect the diverse demands and expertise required across different AI positions. The dynamic nature of this field offers promising financial rewards and substantial career growth opportunities. Understanding the landscape of salary potential is crucial for those considering a career in AI or looking to advance in this domain. This knowledge not only aids in making educated career judgments but also in bargaining better salary. The future of AI continues to be bright, with advancements and innovations promising to create even more opportunities. As the industry evolves, so will the value and demand for skilled AI professionals, making now an excellent time to invest in AI skills and education.
2025-03-24T00:00:00
2025/03/24
https://digitaldefynd.com/IQ/ai-salaries-in-the-us/
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Annual AI Jobs Salary Report: Overviews with Expert Advice - eWEEK
Annual AI Jobs Salary Report: Overviews with Expert Advice
https://www.eweek.com
[ "Liz Ticong", "Written By", "Liz Ticong Is A Tech Industry Expert With Hands-On Experience In Ai", "Software Testing", "Product Analysis. Specializing In Ai News", "Software Reviews", "Buyer S Guides", "She Rigorously Tests", "Experiments With The Latest Ai", "Tech Tools To Provide In-Depth" ]
Salaries for AI-related roles vary based on job title, location, industry, level of expertise, and labor market demand-supply dynamics—but in all cases, they're ...
eWEEK content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More. Artificial intelligence job salaries are growing in parallel with the technology’s adoption into nearly every sector of industry. As AI continues to gain momentum, the demand for skilled professionals will only grow, making AI careers both intellectually fulfilling and financially rewarding. Expertise is valued, but it’s also difficult to find, and professionals with the right skills and experience have the most opportunities available to them. For our AI jobs salary guide, we analyzed a wide range of AI roles and the average compensation they command to help you better understand the job market in this exciting field. KEY TAKEAWAYS As AI adoption accelerates, professionals who can effectively collaborate with intelligent systems are well-positioned to bring more value to employers and secure top-tier salaries.(Jump to Section) Continuous learning and upskilling can maximize earning potential and certifications, advanced degrees, and strong portfolios enhance marketability.(Jump to Section) AI roles offer competitive salary ranges based on experience and expertise.(Jump to Section) AI Jobs Salaries: Comparison Chart We sourced AI jobs salary data for a range of common roles from Glassdoor, a reputable platform for job-seekers and professionals to access salary insights and company reviews. Keep in mind that actual salaries may vary slightly based on a variety of factors, including the size of the company—startup, small business, or large enterprise, for example—and its financial standing. While the artificial intelligence salary ranges listed here represent typical compensation levels for AI roles based on industry standards, individual offers may also vary based on negotiation, location, specific job responsibilities, and other factors. What Studies Show about AI Salaries Recent studies and reports have shed light on the growing impact of AI skills on salaries and career trajectories. These trends point to the increasing value that employers place on AI expertise and the competitive edge it provides for job seekers. Higher Skills, Higher Wages: An Amazon Web Services (AWS) and Access Partnership study found that employers are willing to pay higher wages to employees with AI skills and expertise. This data supports the increasing value placed on AI proficiency in the job market, underscoring a competitive edge for candidates with these specialized skills. An Amazon Web Services (AWS) and Access Partnership study found that employers are willing to pay higher wages to employees with AI skills and expertise. This data supports the increasing value placed on AI proficiency in the job market, underscoring a competitive edge for candidates with these specialized skills. Specialized Knowledge Beats Experience: Microsoft and LinkedIn’s 2024 Work Trend Annual Report showed that 71 percent of leaders would hire a less-experienced candidate with AI skills over a more-experienced one without them. This statistic emphasizes the growing importance of AI skills in recruitment and career advancement, positioning AI knowledge as a notable asset in today’s competitive workforce. Microsoft and LinkedIn’s 2024 Work Trend Annual Report showed that 71 percent of leaders would hire a less-experienced candidate with AI skills over a more-experienced one without them. This statistic emphasizes the growing importance of AI skills in recruitment and career advancement, positioning AI knowledge as a notable asset in today’s competitive workforce. AI Expertise Demands Premium Wages: Additionally, research conducted by the Oxford Internet Institute and Center for Social Data Science at the University of Copenhagen indicates that workers with AI skills command salaries 21 percent higher than average. This salary premium reflects the scarcity of AI talent and the high demand for professionals who can use AI technologies effectively. Salary Ranges of Popular Jobs As AI continues to transform industries globally, the demand for skilled professionals in this field has skyrocketed. AI jobs offer competitive remuneration, diverse career paths, and the opportunity to mold the future of technology. Compensation for AI-related roles can fluctuate based on various factors, including the specific job title, geographic location, and level of expertise. Machine Learning Engineer Machine learning engineers design and implement machine learning algorithms and models to solve specific business problems. Because it already has so many practical applications, machine learning is generally considered to be one of the fastest growing job titles in the AI landscape. Salary increases can come quickly with experience in advanced skills like machine learning frameworks. AI Engineer AI engineers develop and deploy AI systems, including machine learning models and deep learning algorithms. They create algorithms, build AI models, and integrate them into applications and products. The amount you earn leans on your level of experience. AI engineers tend to be employed in the technology, finance, healthcare, and consulting industries. Data Scientist Data scientists are responsible for collecting, analyzing, and interpreting complex data to inform business decisions and strategies. They utilize statistical techniques and machine learning algorithms to derive insights and solve problems. Data scientists require a solid understanding of programming languages like Python or R, as well as expertise in data manipulation and visualization. Experienced data scientists with advanced degrees or specialized skills are in very high demand. Computer Vision Engineer A computer vision engineer specializes in developing algorithms and systems that enable machines to interpret and understand visual information from digital images or videos. They work on tasks such as object detection, image recognition, and video analysis. Computer Vision Engineers often collaborate with software developers and researchers to implement and optimize computer vision solutions for various applications, such as autonomous vehicles, medical imaging, robotics, and augmented reality. Startups and companies focusing on advanced technologies often offer competitive compensation packages with additional perks like stock options. Natural Language Processing Engineer Natural language processing (NLP) engineers develop algorithms and models to enable computers to understand, interpret, and generate human language, or a reasonable facsimile of human speech. They work on tasks such as text classification, sentiment analysis, machine translation, and chatbot development. There are already many highly practical applications of NLP, hence the high salary range at the top end. Deep Learning Engineer A deep learning engineer is a specialized role within the broader field of artificial intelligence and machine learning. These professionals focus on developing and implementing deep neural networks and other machine learning algorithms to solve complex problems like image recognition, natural language processing, and autonomous driving. Due to their high-demand skill set, deep learning engineers command competitive compensation. AI Research Scientist An AI research scientist is at the forefront of developing new algorithms, models, and techniques to advance the field of artificial intelligence. These professionals typically hold advanced degrees in computer science, mathematics, or related fields and are skilled in areas like machine learning, statistics, and data analysis. Because an AI research scientist may do more theoretical work, the pay is not always as high as other AI specialities. Business Development Manager The role of a business development manager in AI is crucial for bridging the gap between technical innovation and market growth. These professionals identify business opportunities, forge strategic partnerships, and drive revenue growth for AI products and services. They play a momentous role in scaling AI solutions and driving adoption among customers. Experience level and track record of successful business development initiatives significantly impact compensation. AI Product Manager AI product managers oversee the development and deployment of AI-powered products and solutions. They collaborate with cross-functional teams, including engineers, designers, and marketers, to define product roadmaps, prioritize features, and ensure alignment with business objectives. Experience in product management coupled with AI expertise commands a premium in this role. AI Consultant AI Consultants provide expert guidance to organizations seeking to leverage AI technologies for business transformation. They assess client needs, design AI solutions, and oversee implementation to deliver tangible outcomes. Salary for AI consultants can vary widely based on consulting firm, experience level, and project scope. Geographic location also influences compensation, with major consulting hubs offering higher salaries. Expert Insights on AI Job Salaries and Careers Insights from industry experts highlight the growing importance of AI expertise across industries, emphasizing the need for continuous learning and upskilling, and the potential impact of AI on job roles and compensation. “The widening pay gap between tech and non-tech roles underscores the influence of AI across industries, suggesting salaries will increasingly revolve around AI expertise,” according to Young Pham, a project manager at BizReport. This showcases how AI skills command higher pay as organizations seek to take advantage of this transformative technology. Sheila Jordan, SVP and Chief Digital Technology Officer for Honeywell, said her company is taking a proactive approach to AI. “We’ve made AI training a priority to ensure everyone can use Copilot and other AI solutions,” she said. “We also launched the GenAI Academy to support employee growth and increase AI ambassadors.” Jordan’s insight stresses the significance of ongoing professional development to stay competitive in the AI job market. The benefits to skills development in this field are clear, even if the future is not. “If your job is affected by AI, your salary might actually increase,” said Sander van’t Noordende, CEO of talent company Randstad. This suggests that as AI automates tasks, the remaining human roles may become more specialized and valuable, leading to higher compensation for those with the skills necessary to work with AI. How Do I Get Paid More as an AI Professional? To increase your earning potential and get paid more as an AI professional, a number of strategies to boost your skills and marketability can be effective. Here are some of the more common ones: Hone Your AI Skills: Continuously improving and refining your skills is key to increasing your value in the job market. Stay updated with the latest AI trends and technologies in your sector. Take online courses, attend workshops, and actively seek opportunities to deepen your expertise. Continuously improving and refining your skills is key to increasing your value in the job market. Stay updated with the latest AI trends and technologies in your sector. Take online courses, attend workshops, and actively seek opportunities to deepen your expertise. Get a Technical Certification: Obtaining relevant AI certifications can significantly boost your credentials and marketability. Certifications validate your expertise and demonstrate your commitment to professional development. Obtaining relevant AI certifications can significantly boost your credentials and marketability. Certifications validate your expertise and demonstrate your commitment to professional development. Get an Advanced Degree: While not always necessary, having an advanced degree (such as a master’s or MBA) can enhance your earning potential, especially in certain fields like business, healthcare, or technology. While not always necessary, having an advanced degree (such as a master’s or MBA) can enhance your earning potential, especially in certain fields like business, healthcare, or technology. Build a Portfolio of Work: Showcase your skills and accomplishments through a strong portfolio. This could include projects you’ve worked on, case studies, articles, or designs. A compelling portfolio demonstrates your capabilities and can differentiate you from other candidates when negotiating higher compensation. Showcase your skills and accomplishments through a strong portfolio. This could include projects you’ve worked on, case studies, articles, or designs. A compelling portfolio demonstrates your capabilities and can differentiate you from other candidates when negotiating higher compensation. Network with Professionals: Attend industry events, join professional associations, and connect with peers and mentors in your field. Networking can lead to new job opportunities, referrals, and valuable insights into salary trends. Attend industry events, join professional associations, and connect with peers and mentors in your field. Networking can lead to new job opportunities, referrals, and valuable insights into salary trends. Negotiate a Higher AI Job Salary: Finally, if you’re offered an AI job, negotiate a higher salary. Research market rates and present your unique skills. Approach discussions confidently and professionally to reach a mutually beneficial outcome. Bottom Line: The Future of AI Salaries is Bright AI jobs can be highly lucrative, especially if you have the right skills, experience, and qualifications. Salaries for AI-related roles vary based on job title, location, industry, level of expertise, and labor market demand-supply dynamics—but in all cases, they’re some of the highest across the tech sector. Studies have also shown that workers with AI capabilities can earn substantially more than their counterparts. The increasing demand for AI expertise is driving the overall salary outlook upward, as organizations are willing to invest in top talent, which remains scarce. To maximize earning potential in AI jobs, you focus on continuous learning, skill development, and staying abreast of industry trends. While many may be afraid that AI will take their jobs, the reality is that AI won’t replace your job—but someone who knows how to work effectively with AI will. Insights from industry experts suggest that upskilling and adapting to the changing landscape may be the key to success. Read our in-depth guide to generative AI companies to learn more about the top 20 leading vendors in this dynamic, still-emerging field.
2024-07-12T00:00:00
2024/07/12
https://www.eweek.com/artificial-intelligence/ai-jobs-salary/
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'Sign-on bonuses of $150m': AI talent war heats up - AFR
‘Sign-on bonuses of $150m’: AI talent war heats up
https://www.afr.com
[ "Melissa Heikkilä", "Clara Murray", "Cristina Criddle", "Primrose Riordan", "Sally Patten", "Mandy Coolen", "John Davidson", "Nick Lenaghan" ]
While some top AI engineers are being paid more than $10 million a year, typical pay packages were between $US3 million and $US7 million – ...
London/San Francisco | The intense battle to poach top artificial intelligence researchers and engineers from rivals has seen a rapid escalation in wages, as tech groups such as Meta and OpenAI race to gain the competitive edge in the fast-developing technology. OpenAI told staff in recent days it is seeking “creative ways to recognise and reward top talent” after losing key employees to rivals, despite industry data suggesting the ChatGPT maker offers salaries near the top of the market. Loading... Financial Times
2025-07-01T00:00:00
2025/07/01
https://www.afr.com/technology/sign-on-bonuses-of-150m-ai-talent-war-heats-up-20250701-p5mbr1
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AI Engineer Salaries in 2025: Comprehensive Guide - Qubit Labs
AI Engineer Salary in 2025: Breakdown by Location, Experience, and Role
https://qubit-labs.com
[ "Oksana Zabolotna", "Updated Jul", "Hbd At Qubit Labs", "Hbd", "Head Of Partnerships At Qubit Labs" ]
The average AI salary in US ranges from $122,665 to $152,950, based on different resources. Glassdoor states that the average AI specialist salary in the USA is ...
In 2025, Artificial Intelligence (AI) will continue to shape the future by being integral to addressing the most complex challenges people face, from healthcare access to the climate change crisis. Between 2023 and 2024, the percentage of company executives and AI decision-makers using generative AI increased from 55% to 75%. AI engineers have become indispensable across various industries, including software engineering, manufacturing, oil and gas, renewable energy, fintech, edtech, and medical technology. Programming, cybersecurity, data science, machine learning (ML), and robotics are the most in-demand skills. Due to the increased demand for AI knowledge across various businesses, an AI engineer salary increased significantly between 2022 and 2024. In August 2022, salaries were $231,000, and by March 2023, they had increased to $268,000. By March 2024, they had risen to $300,600 after somewhat declining to $244,500 in May 2023. How much do AI engineers make in 2025? Qubit Labs conducted in-depth research to help you comprehensively understand the average AI engineer salary worldwide. This article will provide an overview of the salaries by location, expertise, and role. Key Takeaways: Generative AI, multimodal AI, and AI in science and healthcare are the major trends driving the salary for AI engineer. USA, Canada, and Australia offer the highest wages: $147,524 , $110,018 , and $128,047 , respectively. , , and , respectively. In Western Europe, AI engineers earn $74,628 in the UK and $145,560 in Switzerland. in the UK and in Switzerland. Eastern Europe offers ~ $40,000 , on average. , on average. The Artificial Intelligence engineer salary ranges from $17,323 to $114,852 in Asia. in Asia. In Latin America, AI engineers receive $18,547 to $58,075 , depending on the country. , depending on the country. Junior Computer Vision engineers have the highest salary among all AI engineer roles — $140,043 . . Middle NLP engineers command the highest salaries in the industry: $170,000. Senior machine learning engineers earn $212,928 annually. What Is an AI Engineer? AI engineers use their artificial intelligence and machine learning expertise to create computer systems and applications. They contribute to developing more obscure technologies that may not be immediately apparent to a broad audience, such as developing AI assistants, AI surgical robots, and self-driving cars. The required and preferred skills of AI engineers are: Proficiency in machine learning and deep learning. Mastery of Python, Java, C++, TensorFlow, and NLP. Understanding of functional and object-oriented design concepts and best practices. Knowledge of designing and optimizing RDBMSs, NoSQL databases, and REST APIs. A bachelor’s or master’s degree in computer science or a similar discipline. Familiarity with cloud environments. Strong communication and time-management skills. What Does an AI Engineer Do? Depending on the experience level and role, an AI and ML engineer can perform various functions. Here is a brief overview of the primary responsibilities: Creating and implementing machine learning algorithms. Building the infrastructure for data transformation. Using machine learning to automate various processes. Maintaining data security and privacy. Creating and managing AI strategies. Collaborating with proficient engineers and executives to work on functional design, process design, prototyping, training, and testing of ML models. Leading a research team that analyses the automation, AI market, and competitive environment. Ensuring alignment between project teams and stakeholders, providing input, and empowering team members to alter the performance or appearance of the final product as needed. Different Kinds of AI Engineers Artificial intelligence engineering is a diverse and dynamic industry with numerous specialized roles. We’ll consider the most popular ones. Machine Learning Engineers These developers are responsible for designing, building, and optimizing systems that enable AI and ML models to run smoothly and autonomously. They also integrate models into various apps and improve their performance for maximum efficiency. They should be proficient in PyTorch, TensorFlow, and Scikit-Learn to perform these responsibilities. Data Scientists Data scientists use ML algorithms, statistical techniques, and visualization technologies to analyze and interpret large data sets, identify common trends, forecast outcomes, and develop actionable strategies. Their tech stacks include the knowledge of Python, R, NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch, Apache Spark, PostgreSQL/MySQL, MongoDB, and Git/GitHub. Robotics Engineers These specialists design, build, operate, test, and debug robots and robotic systems across various industries, including healthcare, automotive, manufacturing, agriculture, and aerospace. They should be proficient in Python, Java, C/C++, ROS/ROS 2, VEX Robotics, Gazebo, Webots, TensorFlow/PyTorch, Docker, and Jira. Computer Vision Engineers They are highly skilled specialists who develop hardware and software to process visual input and identify objects and people. They interpret large amounts of data to address real-world issues. Their tech expertise includes Python, Java, and C/C++ knowledge, proficiency in TensorFlow/PyTorch, knowledge of image processing techniques (image filtering, feature extraction, segmentation, etc.), mastery of deep learning & neural networks, and understanding of cloud platforms and deployment tools (AWS, Google Cloud, Microsoft Azure) and version control tools (Docker, Git/GitHub). Natural Language Processing (NLP) Engineers These engineers ensure machines can comprehend, interpret, and respond to human language meaningfully and accurately. This is essential for language translation systems, chatbots, and virtual assistants. NLP engineers should know Python, Java, and R and demonstrate a comprehensive understanding of Natural Language Toolkit (NLTK), spaCy, various machine learning and deep learning techniques, and various NLP techniques and methods (NER, tokenization, part-of-speech tagging, etc.) AI Research Scientists AI research scientists investigate, create, and apply advanced AI technologies. Their contributions are essential to expanding AI’s theoretical knowledge and real-world applications. Their roles often involve knowledge of programming languages (Python, Julia, C++, and R), deep learning models (RNNs, CNNs, GANs), TensorFlow, PyTorch, and Scikit-learn, as well as mastery of NLP, generative AI, and computer vision. AI Product Managers AI product managers supervise the development and implementing of AI solutions to ensure that AI-driven solutions meet consumer needs and corporate objectives. They usually collaborate closely with stakeholders, data scientists, and engineers to provide top-notch design and management of the product lifecycle. To perform their duties efficiently, they should know how to develop AI roadmaps and prioritize features, comprehensively understand Python, R, and SQL, and be familiar with NLP models (e.g., BERT), AWS, and Google Cloud. Factors Influencing AI Developer Salaries As in other disciplines, the AI software engineer salary depends on various factors, including location, expertise, education, industry demand, and the type of company they work for. Experience Level In this case, the strategy is the same as for other specialists: skilled AI engineers with more experience typically get better salaries than those just beginning their careers. An entry level AI developer salary in US is $69,362 annually, whereas a senior AI developer salary in the US is $126,557. Educational Background Advanced degrees (Master’s and Ph.D./MD) usually lead to higher-paying opportunities. Salary.com indicates that specialists with a high school diploma or technical certificate are most likely to earn $146,716—$158,116 annually, whereas the artificial intelligence engineer salary for experts with PhD, MD, or equivalent is $155,193—$165,936 annually. Besides, certification in AI and Machine Learning, generative AI for business transformation, and IBM AI Engineering Professional guarantee better career prospects. Location and Regional Trends in Salaries Location and regional demand influence the AI developer salary. Countries with high cost of living and well-developed tech ecosystems, like the USA, Canada, Israel, Switzerland, Germany, Australia, and Singapore, offer significantly higher wages than Eastern European and Latin American countries. Qubit Labs research shows that, on average, the artificial intelligence salary in Eastern Europe is ~70% lower than in the USA, but software development quality remains high. These factors are pivotal for businesses that consider inhouse vs outsource software development. Company Size Large enterprises and tech giants usually offer more competitive salaries due to the increased demand for talent and extensive financial resources. According to ZipRecruiter, the average AI engineer salary in the US is $129,348. Meta, an established player in the global tech scene, offers generative AI developers up to $173,000/year + bonus + equity + benefits. Demand for Specialized Skills Unicorns and mid-size companies are looking for individuals with advanced skills, which results in higher average total compensation. Usually, tech companies are searching for talent with expertise in deep learning (TensorFlow, PyTorch, and CNNs knowledge), NLP (BERT, spaCy), computer vision (OpenCV, YOLO), and big data (Apache Spark, Hadoop, SQL, and NoSQL). This tech stack significantly increases their earning potential. AI Engineer Salaries in the United States The average AI engineering salary in the USA is $147,524. The highest AI software engineer salary is in Boston ($160,261), San Francisco ($125,341), Seattle ($121,070), and Washington ($120,425). NYC offers the average AI/ML engineer salary of $116,390. The base wage ranges from $102,280 to $103,740 in Austin and Atlanta. How Much Does an AI Engineer Make In the United States? The average AI salary in US ranges from $122,665 to $152,950, based on different resources. Glassdoor states that the average AI specialist salary in the USA is $122,665. The additional pay, which may include cash bonus, tips, commission, and profit sharing, is $39,270 annually. Therefore, the total compensation is $161,935 annually. Source: glassdoor.com ZipRecruiter indicates that the average Artificial Intelligence salary in US is $147,524 annually, or $71 per hour. Source: ziprecruiter.com Talent.com shows that the average AI programmer salary is $152,950. The entry-level AI engineer salary in US is $115,059, and a senior AI engineer salary is $204,444 annually. Source: talent.com As for the AI machine learning engineer salary, Indeed states that the average yearly salary is $161,946. San Francisco ($191,665 per year), New York ($186,024), and Santa Clara ($182,797) are the highest-paying cities. Source: indeed.com Here is a short overview of the average AI engineers salary. Which US Cities Offer the Highest AI Engineer Salaries? Nome, AK, offers the highest AI engineer average salary in the country — $183,002 per year, or an equivalent of the Artificial Intelligence salary per month of $15,250. Here is a detailed breakdown of the highest-paying cities in the USA, according to ZipRecruiter. City Annual AI Machine Learning Salary Average Monthly Pay Nome, AK $183,002 $15,250 Cupertino, CA $182,006 $15,167 Berkeley, CA $180,634 $15,052 Redwood City, CA $180,621 $15,051 Sitka, AK $177,719 $14,809 Holdrege, NE $176,713 $14,726 Wyoming, WY $175,940 $14,661 Mountain View, CA $174,031 $14,502 Menlo Park, CA $173,850 $14,487 San Francisco, CA $173,808 $14,484 * Salary data is sourced from ziprecruiter.com Hourly AI Developer Rates by State State Hourly Rates California $50 New York $56 Texas $48 Wisconsin $52 North Carolina $46 South Carolina $45 Colorado $54 Minnesota $52 Georgia $43 Washington $58 New Jersey $52 Utah $47 Connecticut $49 Maine $50 Virginia $51 Massachusetts $77 * Salary data is sourced from ziprecruiter.com Massachusetts offers the highest hourly wage — $77. Washington has $58, New York — $56, and the hourly rate in Colorado — $54. California, Wisconsin, Minnesota, New Jersey, Maine, and Virginia offer almost the same hourly rate — from $50 to $52. Texas, North and South Carolina, Utah, and Connecticut offer hourly pay of $45-$49. Georgia has the lowest AI developer salary in the US — $43 per hour. Average AI Engineer Salary in the World How much do AI developers make? The highest-paying country in the world is the USA, with an average Artificial Intelligence specialist salary of $147,524. Other location based salaries are the following: Canada and Australia offer $110,018 and $128,047 , respectively. , respectively. In Western Europe, Switzerland has the highest wages — $145,560 . . As a top outsourcing destination, Eastern Europe offers competitive salaries ranging from $33,600 in Ukraine to $48,263 in Poland . to . In Asia, Singapore stands out as the country with the highest salary of AI engineer — $114,852 annually . . In Latin America, Mexico offers the highest entry level AI engineer salary of $40,652 and the highest average salary of $58,075. Let’s look at the AI/ML developer salary worldwide. AI Developer Salaries in Western Europe Western Europe boasts extensive expertise in autonomous systems and NLP. DeepMind Technologies Limited, an AI research laboratory focusing on neural networks, language models, and other advanced technologies, has research centers in the UK, France, and Germany. In addition to promoting AI innovation and regulating the technology, Western European governments are also attempting to incorporate AI into public services. Country Salary UK $74,628 Germany $98,756 France $81,807 Switzerland $145,560 * Salary data is sourced from talent.com, salaryexpert.com, and glassdoor.com Switzerland offers the region’s highest Artificial Intelligence software engineer salary — $145,560. Germany, with an average rate of $98,756, is second on the list. France and the UK offer $81,807 and $74,628, respectively. AI Engineer Salaries in Eastern Europe This region is known for its unique automation, machine learning, and computer vision expertise. Poland was one of the leaders in terms of total investment in 2024. Poland, Romania, Ukraine, and Bulgaria offer top-tier AI developers for hire with diverse tech stacks. Businesses can hire Python developers (the primary language for AI development) and C++, R, Java, and Julia specialists to tackle various AI solutions. Country Salary Poland $48,263 Romania $42,000 Bulgaria $36,000 Ukraine $33,600 * Salary data is sourced from salaryexpert.com and Qubit Labs’ research Poland is the region’s leader, with an average generative AI developer salary of $48,263. Romania offers $42,000 to mid-level AI engineers, Bulgaria has $36,000, and Ukraine’s average Artificial Intelligence engineering salary is $33,600. AI Developer Salaries Across Asia Asia is the frontier for AI due to government initiatives and private sector investments; the expertise of the local workforce encompasses deep learning and robotics. According to the Government AI Readiness Index 2024, Singapore leads the world in the Data and Infrastructure (93.14 over the US’s 90.90) and Government (90.96 versus the US’s 89.26) pillars. Country Salary India $17,323 China $82,853 Vietnam $25,150 Japan $64,195 Singapore $114,852 * Salary data is sourced from talent.com, salaryexpert.com, indeed.com, and levels.fyi Singapore is a market leader, with an average salary of AI developer of $114,852 annually. China provides $82,853 to experienced AI developers; the average wage in Japan is $64,195. India and Vietnam offer $17,323 and $25,150, respectively. AI Engineer Salaries in Latin America Latin American companies are increasing their use of AI, especially in retail, finance, and healthcare. Mexico, Argentina, and Brazil focus their national plans on the integration and growth of AI throughout all facets of their economies. They also foster a favorable environment for technology adoption, research, and development. Country Salary Mexico $58,075 Brazil $41,250 Argentina $55,900 Bolivia $18,547 * Salary data is sourced from jobicy.com and Qubit Labs’ research Mexico and Argentina offer the highest salaries in the area — $58,075 and $55,900, respectively. In Brazil, AI engineers make $41,250 annually. In Bolivia, the average AI developer salary is $18,547. AI Developer Salary in Canada Canada has a world-leading AI ecosystem, excelling in development and security. It is a global leader due to its extensive government support and research initiatives. The Canadian AI scene comprises over 670 AI startups and 30 generative AI businesses. Talent.com indicates that the AI developer average salary is $110,018 annually, which equals an AI developer salary per month of $9,158 or $56.42 per hour. Junior AI specialists earn $78,159 annually, whereas senior engineers earn 111.11% more — $165,000 annually. AI Software Developer Salary in Australia Australia’s artificial intelligence (AI) market will be worth US$315 billion by 2028. The Australian government regulates the application and implementation of AI technology across various industries, including healthcare, finance, agriculture, and retail. Multiple universities and organizations drive AI innovation and contribute to its nationwide adoption. How much does AI engineer make in Australia? The average salary is $128,047, according to Talent.com. An AI engineer starting salary is $128,047, and more experienced specialists earn $200,000. AI Developer Salaries by Specialization AI engineers perform various roles depending on their tech stack and their industry. Here is the average salary in the USA by specialization. Role Junior Middle Senior Machine Learning Engineer $71,799 $161,946 $212,928 Data Scientist $64,212 $124,726 $154,374 Robotics Engineer $71,799 $119,363 $200,000 Computer Vision Engineer $140,043 $169,419 $208,000 NLP Engineer $135,000 $170,000 $209,831 AI Research Scientist $107,500 $130,117 $173,000 Neural Network Engineer $89,000 $109,040 $133,500 AI Product Manager $92,500 $159,405 $197,000 * Salary data is sourced from indeed.com, talent.com, and ziprecruiter.com Computer vision engineers have the highest starting salary of $140,043 annually. The lowest AI developer salary is offered to data scientists — $64,212 annually. Mid-level specialists earn from $109,040 to $170,000. A neural network engineer salary is the lowest on our list — $109,040. Computer vision and NLP engineers have the highest earnings: $169,419 and $170,000, respectively. As for senior roles, machine learning engineers command the highest pay — $212,928​​ annually. Robotics engineers, computer vision specialists, and NLP engineers earn between $200,000 and $209,831. Experienced neural network engineers receive the lowest compensation — $133,500. Where to Hire Software Developers in 2025 We created a guide that helps you navigate through software development market and get a closer look at the opportunities they offer in 2025 Download Emerging Trends Impacting AI Developer Salaries The salary for AI engineer depends on the global economy. Global businesses’ increased use of AI drives the demand for qualified talent and increases investment in software development. Machine learning, deep learning, and data science are some of the most in-demand skills for AI professionals, as they significantly enhance their pay scale. Here is a brief overview of the prominent trends leading to premium wages. Trend In-Demand Skills Salary Impact Increased Demand for Generative AI Expertise Deep learning, NLP, Python, PyTorch, TensorFlow, prompt engineering, and computer vision. Higher salaries for specialists proficient in large language models. Rise of AI Ethics and Responsible AI Development Proficiency in machine learning and algorithm development, knowledge of data privacy and security protocols, ethical AI standards, AI governance and policy frameworks, AI system testing and validation techniques, and bias mitigation. AI compliance specialists will earn a premium. Edge AI and On-Device AI TensorFlow Lite, computer vision, edge computing, and model optimization. Engineers skilled in on-device AI optimization will earn a premium. Multimodal AI TensorFlow, PyTorch, CNNS, NLP, speech & audio processing, and multimodal model architectures. Specialists who develop AI models processing multiple data types will be in high demand. AI for Science and Healthcare Understanding healthcare systems; knowledge of compliance, data management, statistical analysis, and proficiency in ML/DL; mastery of Python, R, TensorFlow, PyTorch, AWS, and Azure; and knowledge of bioinformatics and genomics. Biotech companies, research institutions, and startups will offer high salaries to specialists with relevant technical expertise. Building AI Agents Knowledge of Python, Java, and C++; proficiency in Pandas, NumPy, and SQL; and understanding of NLP. Developers who can build autonomous AI agents will experience a significant salary boost. AI & Gen AI in Cybersecurity AI programming and development, data and security management, NLP, and security automation tools (SMAAT, SCM, NIPS, CrowdStrike Falcon, etc.). The salary for artificial intelligence specialists with cybersecurity knowledge will be on the high end of the pay scale. Challenges in Hiring and Retaining AI Talent The tech landscape is highly dynamic and competitive, contributing to intense competition for AI professionals. Businesses should use effective strategies to find and retain exceptional talent. Limited Talent Pool AI technology is evolving rapidly, so businesses constantly search for skilled AI developers. Local talent pools may be limited, and the salary expectations can be high. The best option is to employ offshore developers. Our latest research shows that the primary reasons for hiring remote teams are accessing global expertise (74.3% of tech companies) and cost savings (82.9%). Collaborating with AI developers from cost-effective locations can help you use niche skills at competitive rates and speed up your time-to-market. Qubit Labs knows the needs of businesses leveraging AI technology, and we know how to find the best AI engineers efficiently. We have built a dedicated team for an AI-enhanced customer engagement platform, allowing our clients to swiftly enhance an existing solution and build new features while maintaining a competitive edge. Security and Confidentiality Security and confidentiality are crucial for AI initiatives since they frequently contain sensitive data and proprietary algorithms. To eliminate this issue, ensure all developers adhere to strict security protocols, use only safe communication methods, regularly check compliance rules, and implement robust data protection measures. Retention Challenges Retaining top-tier talent may be as challenging as attracting it. To address this issue, stick to the following strategies. Prioritize training and career development. AI employees should be equipped with the latest AI skills and tools, so organize internal courses, guarantee access to various workshops and seminars, and provide clear career advancement paths. AI employees should be equipped with the latest AI skills and tools, so organize internal courses, guarantee access to various workshops and seminars, and provide clear career advancement paths. Offer competitive compensation packages. If your budget allows, ensure salary and benefits meet the market standards. If you have budget constraints, offer non-monetary benefits like remote work, flexible working hours, a manageable workload, well-being programs, and a generous vacation policy. If your budget allows, ensure salary and benefits meet the market standards. If you have budget constraints, offer non-monetary benefits like remote work, flexible working hours, a manageable workload, well-being programs, and a generous vacation policy. Encourage open communication and productive teamwork to create a collaborative work environment where all professionals feel heard, connected, and dedicated to overall success. Secure Top AI Talent with Qubit Labs AI will be one of the leading technologies in the future, so AI engineer salaries will remain competitive. They will grow based on the latest industry advancements, increasing demand for niche expertise, and the ongoing development of AI-powered solutions. Today, the USA leads the way with the highest AI engineer salary in the world — $147,524. Canada and Australia offer $110,018 and $128,047 to AI developers with 2–5 years of experience. Western Europe offers, on average, ~$100,000 to AI professionals, and Switzerland is the top-paying country in the region. Eastern Europe offers more attractive offshore developer rates while maintaining superior quality. The average pay in major tech hubs is $40,000, approximately 72.89% less than in the USA. In Asia, India and Vietnam offer lower rates ($17,323 and $25,150) than​​ Singapore, which offers AI engineers $114,852. In Latin America, the average AI engineer salary ranges from $18,547 in Bolivia to $58,075 in Mexico. In the future, the demand for skilled professionals with AI expertise and the competition in the market will grow. Businesses should partner with a reliable outstaffing company to build a team that drives innovation now. Qubit Labs has the expertise to source top-tier talent to meet your business needs. Besides, we can conduct free salary research tailored to your requirements to help you make informed decisions. Are you ready to attract top AI talent and revolutionize your industry? Book a free consultation call to learn how.
2025-03-04T00:00:00
2025/03/04
https://qubit-labs.com/ai-engineer-salary-guide/
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AI Engineering Salary: Understanding Compensation Trends in 2025
AI Engineering Salary: Understanding Compensation Trends in 2025
https://nexusitgroup.com
[ "Nexus It Group" ]
Entry-level AI Engineers can expect to earn between $67,000 to $85,000 per year. This starting salary can vary based on location, education, and the specific ...
Artificial Intelligence is reshaping industries and creating new job opportunities. As an AI engineer, you can expect a competitive salary reflecting the skills and expertise required in this fast-growing field. Currently, AI engineers can earn an average annual salary of around $136,620, with some positions offering even higher compensation based on experience and location. This lucrative pay makes AI engineering an attractive career choice for many in the technology sector. Moreover, the salary landscape for AI engineers can vary widely depending on several factors. Your earnings may differ based on your level of experience, industry, and the company you work for. As you navigate this career path, understanding these nuances will help you set realistic salary expectations and identify opportunities for advancement. With the rapid growth of AI technologies, the demand for skilled engineers is expected to rise. Staying updated on salary trends and market insights will empower you in your career. Key Takeaways AI engineering offers competitive salaries that can grow significantly with experience. Salary varies based on location, company, and industry demands. The future of AI engineering is promising, with increasing demand for talent in the field. Understanding AI Engineering AI engineering is a rapidly evolving field that combines software development, data science, and machine learning. You will encounter various roles, needed skills, and educational paths that are essential in this domain. Here’s a closer look at the key aspects of AI engineering. Defining AI Engineer Roles An AI engineer focuses on designing and implementing AI models and algorithms. There are different roles such as Machine Learning engineer, Data Scientist, and Software Engineer. Each role has unique responsibilities but often overlaps in skills. AI Engineer: Creates algorithms for AI applications. Creates algorithms for AI applications. Machine Learning Engineer: Specializes in building and optimizing models. Specializes in building and optimizing models. Data Scientist: Analyzes and interprets complex data. Analyzes and interprets complex data. Data Engineer: Prepares data for analysis and machine learning. Each role requires a solid understanding of machine learning, deep learning, and algorithms. Skills and Specializations To succeed as an AI engineer, you need a blend of technical and soft skills. Key technical skills include: Programming Languages: Proficiency in Python and R is vital. Proficiency in Python and R is vital. Data Handling: Strong skills in data manipulation and analysis. Strong skills in data manipulation and analysis. Algorithms & Models: Understanding of various machine learning models. Understanding of various machine learning models. Deep Learning: Knowledge in neural networks and frameworks like TensorFlow or PyTorch. Knowledge in neural networks and frameworks like TensorFlow or PyTorch. Natural Language Processing (NLP): Useful for applications in language understanding. You may also choose to specialize in areas such as robotics or NLP. This specialization allows you to tailor your expertise to specific industry needs. Education and Certifications A degree in a related field is often necessary for AI engineering roles. Many professionals hold a Master’s Degree in computer science, data science, or artificial intelligence. Educational paths can include: University Degrees: Bachelors or Master’s in AI or related fields. Bachelors or Master’s in AI or related fields. Online Courses: Platforms like Coursera offer specialized courses. Platforms like Coursera offer specialized courses. Certifications: Completing coding boot-camps or professional certifications in machine learning can enhance your credentials. Continual learning is essential as technology evolves. Acquiring these qualifications supports your career growth in AI engineering. AI Engineer Compensation AI engineering is a field with competitive compensation. Your earnings can vary based on several key components, factors affecting salary, and potential additional pay. Salary Components The base salary for an AI engineer in the United States typically ranges around $108,043, according to Glassdoor. However, your average salary can increase with experience and specialization. Mid-level AI engineers average around $147,880 per year, while senior roles can reach up to $163,037, with some positions going as high as $200,000. When considering compensation, look at the total pay range, including base salary and other elements. Many companies offer bonuses, which can further increase your total income. For instance, additional pay could include cash bonuses, profit sharing, and commissions. Factors Affecting Salary Several factors can influence your salary as an AI engineer. Your years of experience play a significant role in determining pay. More experience often means better compensation. Specialization also matters; niches within AI, such as machine learning or data science, may command higher salaries. The industry you work in can impact your earnings, too. Technology companies often provide more competitive compensation packages compared to other sectors. Location is important as well. For example, engineers working remotely may have different salary standards than those in tech hubs. Benefits and Additional Pay Benefits are an essential part of your total compensation package. Many employers offer perks like health care, flexible work hours, and professional development opportunities. These benefits improve your work-life balance. In addition to standard benefits, many companies provide bonuses as part of their compensation strategy. This might include cash bonuses based on performance or project completion. Additional pay can also come from profit sharing, which rewards you for helping the company succeed. Understanding these components will help you make informed decisions about your career and potential earnings in AI engineering. Career and Market Insights The AI engineering job market is dynamic and shows promising trends. Factors like regional demand, technological advancements, and employment projections provide clear insights for your career considerations in this field. Job Market Overview The job market for AI engineers is robust, particularly in major US cities like New York, San Francisco, and Boston. Tech companies are constantly seeking skilled workers to enhance their capabilities in AI and machine learning. According to the US Bureau of Labor Statistics, engineering jobs, especially in AI, are among the fastest-growing occupations. The increasing reliance on AI technologies across various industries drives demand. In cities such as Chicago and Houston, you’ll find numerous opportunities, although salaries can vary significantly. Job Outlook and Growth The job outlook for AI engineers remains strong, with significant growth projected over the next decade. Government data indicates that positions in AI-related fields could grow by as much as 20% by 2031. This surge is driven by advancements in machine learning models and a growing need for AI solutions in businesses. Specific regions, like Silicon Valley in San Francisco, often see higher demand for AI expertise, leading to competitive salaries. Meanwhile, cities like Boston are also becoming tech hubs, attracting talent and investment in AI technologies. High-Demand AI Specialties Within AI engineering, certain specialties are more sought after. Areas such as machine learning, natural language processing, and computer vision are in high demand. Companies are looking for professionals who can build efficient machine learning models. Roles such as data scientist and machine learning engineer often command higher salaries in tech-centric areas. In 2025, AI engineers with specialized skills may earn salaries reaching up to $300,000, particularly in competitive job markets. Understanding these specialties can help you tailor your skills to meet industry needs. Salaries by Location and Company Salaries for AI engineers can vary greatly based on location and the company you work for. Understanding these differences will help you make informed career decisions. Geographic Variations In the United States, salaries for AI engineers differ significantly by region. Major cities often offer the highest pay. For example, in San Francisco, the average salary can reach around $300,600, heavily influenced by the high cost of living. New York City also ranks high, with salaries averaging about $268,000. In contrast, cities like Chicago and Houston tend to offer lower salaries than coastal hubs. In Boston, mid-level AI engineers may earn about $147,880. Geographic location plays a crucial role in determining your compensation due to demand, cost of living, and company presence. Top Paying Companies Some companies consistently pay higher salaries for AI engineering roles. Google, Amazon, and Apple are among the top payers in the industry. For instance, Google offers average salaries around $247,200 for AI-focused software engineers. Microsoft also competes for talent with salaries often exceeding $200,000 for experienced engineers. Companies in sectors like finance and healthcare are also known to offer competitive salaries to attract skilled AI professionals. Researching specific companies can give you insights into potential earnings in your desired field. Understanding Pay Data When examining AI engineering salaries, it’s important to look at various sources of pay data. This information often comes from salary surveys and official reports, providing insights into how compensation varies across roles, experience levels, and locations. Analyzing Salary Surveys Salary surveys are useful for gathering information from professionals in the field. These surveys often collect data submitted anonymously, allowing employees to share their compensation without fear. Websites like Glassdoor are popular for providing salary estimates based on user submissions. You can find median salaries and the most likely range for AI engineers. For example, mid-level AI engineers typically earn around $147,880, while senior roles can reach $163,037. This data reflects trends in the tech industry and helps you understand where you stand compared to others in similar positions. Government and Industry Reports Government and industry reports offer reliable data on compensation trends. The US Bureau of Labor Statistics (BLS) regularly publishes salary data for various roles, including AI engineers. According to these reports, the median salary for AI engineers is approximately $136,620. These figures are crucial for making informed career decisions. They present a broader view of salary ranges across different regions and job levels. In addition to median salaries, these reports often outline compensation packages that include bonuses and stocks, helping you to assess the full value of your potential earnings. Future of AI Engineering Salaries As the demand for AI skills grows, the salaries for AI engineers are likely to change. Key economic trends and evolving pay scales will shape what you can expect in the future. Economic Trends Impacting Salaries Several economic factors influence AI engineering salaries. The global economy is embracing AI, which is driving demand for skilled professionals. Companies are investing heavily in software development to integrate AI and machine learning into their systems. Skills in demand include machine learning and data science. These skills are becoming essential as businesses look for innovative solutions. Your transferable skills, such as problem-solving and programming, can improve your earning potential. Inflation rates and labor market dynamics also play a role. Increased competition for AI talent pushes salaries higher. Predicting the Evolution of AI Pay Scales AI pay scales are expected to evolve as the industry grows. More senior roles, such as principal machine learning engineers, may see significant salary growth. Current data shows that average compensation for experienced AI engineers can reach up to $200,000 per year. Total pay ranges could expand as firms offer more bonuses and stock options. As AI becomes integral to business strategies, salaries for related roles like software developers and data scientists will likely increase as well. Keeping up with skill development will be important for maintaining competitive salaries in this fast-evolving field. Comparative Salary Analysis Salaries for AI engineers and their non-AI counterparts differ significantly. Understanding these differences can help you navigate your career choices in the tech field. Below is a detailed look at the salary landscape for AI and non-AI roles. AI vs Non-AI Career Path Salaries AI engineers are among the highest-paid professionals in the tech industry. On average, AI-focused Software Engineers earn $247,200 annually in the U.S. This high demand stems from the complexity and skill required in artificial intelligence roles. In comparison, Software Engineers and Software Developers earn around $134,145 and $127,330 respectively. These figures indicate that specializing in AI can lead to substantially higher compensation due to the technical expertise and advanced knowledge required. Key Comparison: AI Engineer: $247,200 $247,200 Software Engineer: $134,145 $134,145 Software Developer: $127,330 These numbers highlight the financial benefits of pursuing a career in AI. Salaries In Relation to Other Tech Sectors When comparing AI to other tech sectors, the salary for AI roles stands out. For example, Machine Learning Engineers also command competitive salaries, typically in the range of $150,000 to $200,000. This mirrors the trend of high demand for skills in AI and machine learning. In the broader Information Technology field, roles such as IT Managers and Network Administrators often earn between $90,000 and $120,000. This shows a clear gap between general tech roles and positions focused on AI. Tech Sector Salary Examples: Machine Learning Engineer: $150,000 – $200,000 $150,000 – $200,000 IT Manager: $90,000 – $120,000 These comparisons underscore the lucrative potential of AI-focused careers within the tech industry. Frequently Asked Questions In this section, you will find answers to common questions about AI engineering salaries. These questions focus on average salaries, entry-level earnings, impacts of experience, location differences, and salary variations across sectors. What is the average annual salary for an AI Engineer in the United States? The average salary for an AI Engineer in the United States is around $108,043, according to various sources. Some estimates place the average total pay, including bonuses and benefits, at approximately $201,480 per year. How much does an entry-level AI Engineer typically earn? Entry-level AI Engineers can expect to earn between $67,000 to $85,000 per year. This starting salary can vary based on location, education, and the specific company you work for. What are the salary ranges for AI Engineers working at major tech companies like Google? AI Engineers at major tech companies like Google typically earn higher salaries. They often range from $120,000 to over $160,000, depending on their experience level and specific role within the company. Can AI Engineers expect to see their salaries increase with experience? Yes, AI Engineers can see significant salary increases with experience. Mid-level engineers average about $147,880, while senior roles can earn upwards of $163,000 or more. How does location, such as California, impact the salary of an AI Engineer? Location plays a crucial role in the salary of AI Engineers. For example, engineers in California, especially in tech hubs like Silicon Valley, often earn higher salaries compared to those in other states due to the high cost of living and demand for tech talent. Are there significant salary differences between AI Engineers in different sectors? Yes, salary differences do exist between sectors. For instance, AI Engineers working in finance or healthcare may earn more than those in education or non-profit sectors due to the varying demands and complexities of the roles.
2024-08-06T00:00:00
2024/08/06
https://nexusitgroup.com/ai-engineering-salary-understanding-compensation-trends/
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AI at Payscale - Salary Comparison, Salary Survey, Search Wages
Payscale - Salary Comparison, Salary Survey, Search Wages
https://www.payscale.com
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Payscale harnesses the power of AI to boost your productivity, using advanced algorithms and technology vetted by Data Science experts.
The future of compensation is here! Payscale harnesses the power of AI to boost your productivity, using advanced algorithms and technology vetted by Data Science experts. That way, you have more time to focus on higher-impact work, and make decisions to attract and engage employees. After all, your organization’s biggest investment is employee compensation, and we want to help you maximize their productivity and potential. Don’t get left behind.
2022-12-01T00:00:00
https://www.payscale.com/products/software/ai-at-payscale
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Artificial Intelligence Salaries [By Job, Region, Education & More]
Artificial Intelligence Salaries [By Job, Region, Education & More]
https://onlinedegrees.sandiego.edu
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According to Datamation, the average salary for an artificial intelligence programmer is between $100,000 and $150,000. AI engineers, on the other hand, earn an ...
In a world where technology seems to become more sophisticated by the minute, the demand for artificial intelligence jobs is growing — and fast. The Enterprisers Project reports that artificial intelligence will create 133 million new jobs by 2022, and a recent survey from Dun & Bradstreet revealed that 40 percent of the respondents’ organizations are adding more jobs as a result of using artificial intelligence. Rob Toews, a venture capitalist at Highland Capital Partners, writes about artificial intelligence for Forbes. In a recent article about the current and future state of AI, he said this: “If anything, this breakneck pace is only accelerating. Five years from now, the field of AI will look very different than it does today. Methods that are currently considered cutting-edge will have become outdated; methods that today are nascent or on the fringes will be mainstream.” In this guide, learn more about the most common jobs within the ever-growing field of artificial intelligence, including salary ranges, top companies looking for the top AI talent and tips for increasing your AI salary. AI Salary Overview The demand for artificial intelligence jobs is extremely high, with many salaries well into six figures. The exact numbers will depend on many factors, including the specific job responsibilities, industry, experience, education level and geographic location. But here is a typical range: On the lower end, Indeed reports that a research engineer will make approximately $125,695 per year with a machine learning engineer making around $166,574. According to Datamation, the average salary for an artificial intelligence programmer is between $100,000 and $150,000. AI engineers, on the other hand, earn an average of $171,715 with the top earners making more than $250,000. Datamation explains that these high salaries are due to a rare combination of skills and the need for advanced degrees. Comparison Table The need for skilled artificial intelligence professionals spans almost all industries, public agencies and nonprofits, with particularly strong demand and opportunity in such fields as: Financial services Health care Technology and home automation Media Marketing Manufacturing National security Government and military IoT-enabled systems Retail Now let’s break down the most common jobs within artificial intelligence: Job Title Education Years of Experience Average Salary Research Scientist Expected to have a master’s or doctoral degree in computer science or a related technical field that’s supported by experience.* The ability to demonstrate “extensive knowledge and experience” in the following areas: computer perception, graphical models, reinforcement learning and natural language processing.* $101,114 Software Engineer Bachelor’s in software engineering, software development, computer programming, computer science, mechanical engineering. Entry-level roles may require only an associate degree and/or experience in a technical bootcamp.+++ $123,682 AI Engineer Bachelor’s degree in computer science, mathematics, information technology, statistics, finance or economics.++ Master’s degree in computer science, math, cognitive science, data science, artificial intelligence 5 years of experience (preferably more) in numerous programming languages.+ Range of $114,000 to $141,000 Machine Learning Engineer Hiring companies prefer a master’s or doctoral degree in math, computer science, or AI.* Background in applied research and data science* Entry-level engineers typically have 0-4 years of experience; mid-level engineers have 5-9 years of experience and senior positions have 10+ years of experience $166,574 Data Scientist Advanced degree in computer science is preferred.* At least 2 years of experience in machine learning.* “Highly experienced in statistical computing languages and programming languages.”* Also, knowledge and experience related to cloud tools is a plus.* $126,927 Business Intelligence (BI) Developer A bachelor’s in engineering, computer science or a related field is required. A combination of experience and certifications is desired.* “Considerable experience” in the following: data warehouse design, data mining, SQL queries, SQL Server Integration Services, SQL Server Reporting Services, and BI technologies.* $107,880 Big Data Engineer/Architect Preference is given to those who have completed a Ph.D. in mathematics, computer science or a related field.* The ability “to demonstrate significant programming experience” with the following: C++, Java, Python and Scala.* Also, in-depth knowledge and experience related to data mining, data visualization and data migration.* $130,674 *Springboard Blog 5 Careers in Artificial Intelligence + freelancermap Career Insights: What Does an AI Engineer Do? ++Springboard Blog How to Become an AI Engineer +++Glassdoor How to Get a Job as a Software Engineer It’s also important to note that certain AI positions may also require you to obtain a TS/SCI clearance. AI Salary by Region & State Many AI positions are concentrated in key U.S. cities and states with booming tech centers. According to TechRepublic, the top states and their respective cities for artificial jobs are: State Top City/Cities California San Jose, San Francisco, Los Angeles, San Diego District of Columbia Washington, D.C. Washington Seattle New York New York City Massachusetts Boston Illinois Chicago Texas Austin, Dallas It’s probably no surprise that California tops the list as four major metro areas in the state are listed in its top 15 list. According to Built In San Francisco, some of the biggest names in technology call Silicon Valley home, including: Apple Hewlett Packard Google Oracle Intel Cisco Facebook Broadcom Adobe eBay TechRepublic also “found that states with the most AI jobs tend to have strong tech, healthcare, or government sectors.” The Enterprisers Project reinforces that fact, listing New York, San Francisco, Washington, D.C., San Jose and Seattle at the top of the AI job market. “Many West Coast-based tech companies (such as Amazon, Facebook, and Google) have a significant presence in the region. And New York has its share of AI-related tech startups.” In a recent LinkedIn search for artificial intelligence positions, the following locations offered the most results: Seattle (4,364) San Francisco (3,410) Boston (3,095) New York City (1,433) Chicago, IL (1,261) Now let’s analyze the salary for a specific AI position. As you will see, the salary will vary depending on the location, but it’s also important to remember that each position may require varying levels of experience and education. The highest paying U.S. cities for a machine learning engineer, according to Udacity are: San Francisco Bay Area – $187,353 Bellevue, WA – $173,241 San Francisco, CA – $172,138 Boston, MA – $166,513 New York, NY – $153,590 Top Companies Hiring for AI Positions According to TechRepublic, here are some of the top companies that are recruiting for AI positions: Microsoft Nvidia JD.com Google Intel SAP Accenture Nokia Of course there are many more. A recent search for “artificial intelligence” job openings on LinkedIn revealed more than 49,000 results at a wide variety of companies, some of which are cited below. (You can see similar LinkedIn search results here.) Amazon Deloitte Lockheed Martin Booz Allen Hamilton Hewlett Packard Enterprise Johnson & Johnson Fidelity Investments Thermo Fisher Scientific PlayStation Tik Tok UPS Uber Wayfair Warner Bros. Entertainment How to Boost Your AI Salary Advance your hard skills or learn new ones Different AI positions will likely require different hard skills, but all will demand a variety of technical and data-driven abilities. For example, a machine learning engineer should have experience with programming languages such as Java, Python and Scala. A data scientist needs to understand big data platforms. If you’re just starting out, it’s beneficial to take courses that cover Bayesian networking, computer science, cognitive science theory, engineering, physics, robotics and varying levels of math, according to Springboard. Improve and develop your soft skills Indeed defines soft skills as “personal habits and traits that shape how you work, on your own and with others.” No matter the job or position, soft skills are essential for success — especially in an evolving industry like artificial intelligence. “Data computation, mathematics and algorithms are required skills to create artificial intelligence. But AI has a human aspect to it as well,” explains Springboard. “It is made to interpret and adapt to human behavior, and give responses that feel similar to human responses.” That’s where your soft skills come in. For example, critical thinking, creativity, curiosity, the aptitude to work under pressure and the ability to collaborate are all important for varying AI positions. Do your research It’s important to know what your position is worth, especially in terms of location, so that you’re as prepared as possible for any salary negotiation. Consult top job websites such as Indeed, Glassdoor, PayScale and LinkedIn for more information. Earn certifications Certification programs will not only provide valuable education but also add to your experience, knowledge and skillset — all of which may translate to an increased salary. For example, TechRepublic’s 7 recommended data science certifications include the IBM Data Science Professional Certificate, SAS data scientist certifications, Oracle Business Intelligence Certification and more. A Data Analytics and Visualization Certificate is also a good option. Advance your education with a master’s degree One of the best ways to boost your AI salary is through advanced education. A master’s degree will help you achieve a deeper understanding of AI concepts, topics and theories. It’s also a valuable way to gain first-hand experience and meet other professionals in the industry. All of this can translate to helping you gain an important advantage in the job market. “With most degrees, you can increase your earning power within your profession as you move up from a bachelor’s to a master’s to a doctorate,” according to The Balance Careers blog. According to Datamation, “35 percent of AI positions require a Ph.D. and 26 percent require a master’s degree. Why? Because AI is a rapidly growing field and when you study at the Ph.D. level and participate in academic projects, they tend to be cutting edge if not bleeding edge, and that gives the student the experience they need for the work environment.” Download Our Comprehensive Checklist for Choosing the Right AI Degree Program Educational Preparation in Artificial Intelligence High-paying career opportunities in AI and related disciplines continued to expand across a variety of industries. The University of San Diego — a highly regarded industry thought leader and education provider — offers an innovative, online AI master’s degree program, the Master of Science in Applied Artificial Intelligence, which is designed to prepare graduates for success in this important fast-growing field. This program includes a significant emphasis on real-world applications, ethics, privacy, moral responsibility and social good in designing AI-enabled systems.
2021-03-24T00:00:00
2021/03/24
https://onlinedegrees.sandiego.edu/artificial-intelligence-salary-guide/
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2025 AI Engineer Salary in US | Built In
2025 AI Engineer Salary in US
https://builtin.com
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The average salary for a AI Engineer with 7+ years of experience is $185,833. The average salary for <1 year of experience is $80,000. AI Engineer ...
How Much Does a AI Engineer Make in US? The average salary for a AI Engineer in US is $175,262. The average additional cash compensation for a AI Engineer in US is $35,333. The average total compensation for a AI Engineer in US is $210,595. AI Engineer salaries are based on responses gathered by Built In from anonymous AI Engineer employees in US.
2022-12-01T00:00:00
https://builtin.com/salaries/us/ai-engineer
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Google AI Engineer Salary | $205K-$347K+ | Levels.fyi
Google AI Engineer Salary
https://www.levels.fyi
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AI Engineer compensation in United States at Google ranges from $205K per year for L3 to $347K per year for L5.
Stock Type RSU At Google, RSUs are subject to a 4-year vesting schedule: 38 % vests in the 1st - YR ( 3.17 % monthly ) 32 % vests in the 2nd - YR ( 2.67 % monthly ) 20 % vests in the 3rd - YR ( 1.67 % monthly ) 10 % vests in the 4th - YR ( 0.83 % monthly ) Google commonly refers to RSU as GSU (Google Stock Unit). Although the name is different, it is the same as RSU's. Google's Vesting Schedule may vary between monthly and quarterly vesting depending on the number of shares you recieve: less than 32 GSUs (Annually), 32 - 63 GSUs (Semi-annually), 64 - 159 GSUs (Quarterly) and 160+ GSUs (Monthly).
2022-12-01T00:00:00
https://www.levels.fyi/companies/google/salaries/software-engineer/title/ai-engineer
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Artificial Intelligence (AI): Salaries Heading Skyward - Towards AI
Artificial Intelligence (AI): Salaries Heading Skyward
https://towardsai.net
[ "Stacy S." ]
No information is available for this page. · Learn why
Artificial Intelligence (AI): Salaries Heading Skyward While the average salary for a Software Engineer is around $100,000 to $150,000, to make the big bucks you want to be an AI or Machine Learning (Specialist/Scientist/Engineer.) Stacy S. 6 min read · Aug 29, 2018 -- 12 Listen Share August 29, 2018, by Stacy Stanford — Last updated: May 20, 2020 Artificial intelligence salaries benefit from the perfect recipe for a sweet paycheck: a hot field and high demand for scarce talent. It’s the ever-reliable law of supply and demand, and right now, anything artificial intelligence-related is in very high demand. According to Indeed.com, the average IT salary — the keyword is “artificial intelligence engineer” — in the San Francisco area ranges from approximately $134,135 per year for “software engineer” to $169,930 per year for “machine learning engineer.” 📚 Check out our editorial recommendations on the best machine learning books. 📚 However, it can go much higher if you have the credentials firms need. One tenured professor was offered triple his $180,000 salary to join Google, which he declined for a different teaching position. However, the record, so far, was set in April when the Japanese firm Start Today, which operates the fashion-shopping site Zozotown, posted new job offerings for seven “genius” AI tech experts, offering annual salaries of as much as 100 million yen, or just under USD 1 million. Critical Sectors for AI Salaries Scoring a top AI salary means working in the “right” sector. While plentiful, AI jobs are mainly in just a few sectors — namely tech — and confined to just a few big and expensive cities. Glassdoor, another popular job search site, notes that 67% of all AI jobs listed on its site are located in the Bay Area, Seattle, Los Angeles, and New York City. It also listed Facebook, NVIDIA, Adobe, Microsoft, Uber, and Accenture as the five best AI companies to work for in 2018, with almost 19% of open AI positions. The average annual base pay for an AI job listed on Glassdoor is $111,118 per year. Glassdoor also found that financial services, consulting, and government agencies are actively hiring AI engineering and data science professionals. This includes top firms like Capital One, Fidelity, Goldman Sachs, Booz Allen Hamilton, EY, and McKinsey & Company, NASA’s Jet Propulsion Laboratory, the US Army, and the Federal Reserve Bank. However, expect the number of jobs and fields to expand considerably soon. A recent report from Gartner said that AI would kill off 1.8 million jobs, mostly menial labor, but the field oughts to create 2.3 million new jobs by 2020, such statement is emphasized by a recent Capgemini report that found that 83% of companies using AI say they are adding jobs because of AI. Best Jobs for AI Salaries The term “AI” is rather broad and covers several disciplines and tasks, including natural language generation and comprehension, speech recognition, chatbots, machine learning, decision management, deep learning, biometrics, and text analysis and processing. Given the level of specialization each requires, not many professionals can master more than one discipline. In short, finding the best AI salary calls for actively nurturing the right career path. While the average pay for an AI programmer is around $100,000 to $150,000, depending on the region of the country, all of these are in the developer/coder realm. To make big money, you want to be an AI engineer. According to Paysa, yet another job search site, an artificial intelligence engineer, earns an average of $171,715, ranging from $124,542 at the 25th percentile to $201,853 at the 75th percentile, with top earners making more than $257,530. Why so high? Because many come from non-programming backgrounds. The IEEE notes that people with PhDs in sciences like biology and physics are returning to school to learn AI and apply it to their field. They need to straddle the technical, knowing a multitude of languages and hardware architectures, with an understanding of the data involved. The latter makes engineers rare and thus expensive. Why Are AI Salaries So High? The fact is, AI is not a discipline you can teach yourself as many developers do. A survey by Stack Overflow found 86.7% of developers were, in fact, self-taught. However, that is for languages like Java, Python, and PHP, not the esoteric art of artificial intelligence. It requires advanced degrees in computer science, often a Ph.D. In a report, Paysa found that 35 percent of AI positions require a Ph.D., and 26 percent require a master’s degree. Why? Because AI is a rapidly growing field and when you study at the Ph.D. level and participate in academic projects, they tend to be innovative if not bleeding edge, and that gives the student the experience they need for the work environment. Moreover, it requires multiple disciplines, including Python, C++, STL, Perl, Perforce, and APIs like OpenGL and PhysX. Besides, because the AI is doing important calculations, a background in physics or some kind of life science is necessary. Therefore, to be an effective and in-demand AI developer, you need a lot of skills, not just one or two. Indeed lists the top 10 skills you need to know for AI: 1) Machine learning 2) Python 3) Statistics 4) Data science 5) Hadoop 6) Big Data 7) Java 8) Data mining 9) Spark 10) R As you can see, that is a wide range of skills, and none of them is learned overnight. According to The New York Times, there are fewer than 10,000 qualified AI specialists in the world. Element AI, a Montreal company that consults on machine learning systems, published a report earlier this year that 22,000 Ph.D.-level computer scientists in the world are capable of building AI systems. Either way, that is too few for the demand reported by Machine Learning News. Competing Employers Drive Salaries Higher With so few AI specialists available, tech companies are raiding academia. At the University of Washington, six of 20 artificial intelligence professors are now on leave or partial leave and working for outside companies. In the process, they are limiting the number of professors who can teach the technology, causing a vicious cycle. US News and World Report list the top 20 schools for AI education. The top five are: 1) Carnegie Mellon University, Pittsburgh, PA 2) Massachusetts Institute of Technology, Cambridge, MA 3) Stanford University, Stanford, CA 4) University of California — Berkeley, Berkeley, CA 5) The University of Washington, Seattle, WA With academia being raided for talent, alternatives are popping up. Google, which is hiring any AI developer it can get its hands on, offers a course on deep learning and machine-learning tools via its Google Cloud Platform Website, and Facebook, also deep in AI, hosts a series of videos on the fundamentals of AI such as algorithms. If you want to take courses online, there is Coursera and Udacity. Basic computer technology and math backgrounds are the backbones of most artificial intelligence programs. Linear algebra is as necessary as a programming language since machine learning performs analysis on data within matrices, and linear algebra is all about operations on matrices. According to Computer Science Degree Hub, coursework for AI involves the study of advanced math, Bayesian networking, or graphical modeling, including neural nets, physics, engineering and robotics, computer science, and cognitive science theory. Some things cannot be taught. Working with artificial intelligence does not mean you get to offload the work on the computer. It requires analytical thought process, foresight about technological innovations, technical skills to design, the skill to maintain and repair technology and software programs as well as algorithms. Therefore, it is easy to see why skilled people are so rare — which drives AI salaries only higher.
2021-02-08T00:00:00
2021/02/08
https://towardsai.net/p/artificial-intelligence/artificial-intelligence-salaries-heading-skyward-e41b2a7bba7d
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AI Influence on US Workforce Salaries - Biz Report
AI Influence on US Workforce Salaries
https://www.bizreport.com
[]
AI-related jobs offer 77.53% higher pay than other occupations. This salary disparity is most noticeable at the entry-level, where AI-related jobs boast an ...
State-by-state AI jobs salary comparison When analyzing AI worker salaries across the United States, our data revealed distinct regional variations. Connecticut, California, South Carolina, Louisiana, and Minnesota have emerged as the top-paying states for AI professionals. Connecticut has the highest average AI wage with over $176k a year. On the other hand, Tennessee reports the lowest AI worker wages in the U.S., averaging $84,190 annually. However, even with this seemingly lower figure, the pay is still greater than the average wage in 39 states for other occupations. Guam has the best AI salaries compared to all occupations, coming in at 167% more than other occupations in the state. On the other hand Maryland has the lowest AI salaries compared to other occupations, with AI jobs earning only 3.3% more. AI jobs in 10 states make over 100% more than the average salary in those states. This signals the financial attractiveness of AI jobs, even in states where the overall salary landscape may differ. The following table gives a numeric contrast of the average salaries by state.
2022-12-01T00:00:00
https://www.bizreport.com/business/ai-influence-on-us-workforce-salaries
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Introducing pay per crawl: enabling content owners to charge AI ...
Introducing pay per crawl: Enabling content owners to charge AI crawlers for access
https://blog.cloudflare.com
[]
Pay per crawl is a new feature to allow content creators to charge AI crawlers for access to their content.
5 min read A changing landscape of consumption Many publishers, content creators and website owners currently feel like they have a binary choice — either leave the front door wide open for AI to consume everything they create, or create their own walled garden. But what if there was another way? At Cloudflare, we started from a simple principle: we wanted content creators to have control over who accesses their work. If a creator wants to block all AI crawlers from their content, they should be able to do so. If a creator wants to allow some or all AI crawlers full access to their content for free, they should be able to do that, too. Creators should be in the driver’s seat. After hundreds of conversations with news organizations, publishers, and large-scale social media platforms, we heard a consistent desire for a third path: They’d like to allow AI crawlers to access their content, but they’d like to get compensated. Currently, that requires knowing the right individual and striking a one-off deal, which is an insurmountable challenge if you don’t have scale and leverage. What if I could charge a crawler? We believe your choice need not be binary — there should be a third, more nuanced option: You can charge for access. Instead of a blanket block or uncompensated open access, we want to empower content owners to monetize their content at Internet scale. We’re excited to help dust off a mostly forgotten piece of the web: HTTP response code 402 . Introducing pay per crawl Pay per crawl, in private beta, is our first experiment in this area. Pay per crawl integrates with existing web infrastructure, leveraging HTTP status codes and established authentication mechanisms to create a framework for paid content access. Each time an AI crawler requests content, they either present payment intent via request headers for successful access ( HTTP response code 200 ), or receive a 402 Payment Required response with pricing. Cloudflare acts as the Merchant of Record for pay per crawl and also provides the underlying technical infrastructure. Publisher controls and pricing Pay per crawl grants domain owners full control over their monetization strategy. They can define a flat, per-request price across their entire site. Publishers will then have three distinct options for a crawler: Allow: Grant the crawler free access to content. Charge: Require payment at the configured, domain-wide price. Block: Deny access entirely, with no option to pay. An important mechanism here is that even if a crawler doesn’t have a billing relationship with Cloudflare, and thus couldn’t be charged for access, a publisher can still choose to ‘charge’ them. This is the functional equivalent of a network level block (an HTTP 403 Forbidden response where no content is returned) — but with the added benefit of telling the crawler there could be a relationship in the future. While publishers currently can define a flat price across their entire site, they retain the flexibility to bypass charges for specific crawlers as needed. This is particularly helpful if you want to allow a certain crawler through for free, or if you want to negotiate and execute a content partnership outside the pay per crawl feature. To ensure integration with each publisher’s existing security posture, Cloudflare enforces Allow or Charge decisions via a rules engine that operates only after existing WAF policies and bot management or bot blocking features have been applied. Payment headers and access As we were building the system, we knew we had to solve an incredibly important technical challenge: ensuring we could charge a specific crawler, but prevent anyone from spoofing that crawler. Thankfully, there’s a way to do this using Web Bot Auth proposals. For crawlers, this involves: Generating an Ed25519 key pair, and making the JWK -formatted public key available in a hosted directory Registering with Cloudflare to provide the URL of your key directory and user agent information. Configuring your crawler to use HTTP Message Signatures with each request. Once registration is accepted, crawler requests should always include signature-agent , signature-input , and signature headers to identify your crawler and discover paid resources. GET /example.html Signature-Agent: "https://signature-agent.example.com" Signature-Input: sig2=("@authority" "signature-agent") ;created=1735689600 ;keyid="poqkLGiymh_W0uP6PZFw-dvez3QJT5SolqXBCW38r0U" ;alg="ed25519" ;expires=1735693200 ;nonce="e8N7S2MFd/qrd6T2R3tdfAuuANngKI7LFtKYI/vowzk4lAZYadIX6wW25MwG7DCT9RUKAJ0qVkU0mEeLElW1qg==" ;tag="web-bot-auth" Signature: sig2=:jdq0SqOwHdyHr9+r5jw3iYZH6aNGKijYp/EstF4RQTQdi5N5YYKrD+mCT1HA1nZDsi6nJKuHxUi/5Syp3rLWBA==: Accessing paid content Once a crawler is set up, determination of whether content requires payment can happen via two flows: Reactive (discovery-first) Should a crawler request a paid URL, Cloudflare returns an HTTP 402 Payment Required response, accompanied by a crawler-price header. This signals that payment is required for the requested resource. HTTP 402 Payment Required crawler-price: USD XX.XX The crawler can then decide to retry the request, this time including a crawler-exact-price header to indicate agreement to pay the configured price. GET /example.html crawler-exact-price: USD XX.XX Proactive (intent-first) Alternatively, a crawler can preemptively include a crawler-max-price header in its initial request. GET /example.html crawler-max-price: USD XX.XX If the price configured for a resource is equal to or below this specified limit, the request proceeds, and the content is served with a successful HTTP 200 OK response, confirming the charge: HTTP 200 OK crawler-charged: USD XX.XX server: cloudflare If the amount in a crawler-max-price request is greater than the content owner’s configured price, only the configured price is charged. However, if the resource’s configured price exceeds the maximum price offered by the crawler, an HTTP 402 Payment Required response is returned, indicating the specified cost. Only a single price declaration header, crawler-exact-price or crawler-max-price , may be used per request. The crawler-exact-price or crawler-max-price headers explicitly declare the crawler's willingness to pay. If all checks pass, the content is served, and the crawl event is logged. If any aspect of the request is invalid, the edge returns an HTTP 402 Payment Required response. Financial settlement Crawler operators and content owners must configure pay per crawl payment details in their Cloudflare account. Billing events are recorded each time a crawler makes an authenticated request with payment intent and receives an HTTP 200-level response with a crawler-charged header. Cloudflare then aggregates all the events, charges the crawler, and distributes the earnings to the publisher. Content for crawlers today, agents tomorrow At its core, pay per crawl begins a technical shift in how content is controlled online. By providing creators with a robust, programmatic mechanism for valuing and controlling their digital assets, we empower them to continue creating the rich, diverse content that makes the Internet invaluable. We expect pay per crawl to evolve significantly. It’s very early: we believe many different types of interactions and marketplaces can and should develop simultaneously. We are excited to support these various efforts and open standards. For example, a publisher or new organization might want to charge different rates for different paths or content types. How do you introduce dynamic pricing based not only upon demand, but also how many users your AI application has? How do you introduce granular licenses at internet scale, whether for training, inference, search, or something entirely new? The true potential of pay per crawl may emerge in an agentic world. What if an agentic paywall could operate entirely programmatically? Imagine asking your favorite deep research program to help you synthesize the latest cancer research or a legal brief, or just help you find the best restaurant in Soho — and then giving that agent a budget to spend to acquire the best and most relevant content. By anchoring our first solution on HTTP response code 402, we enable a future where intelligent agents can programmatically negotiate access to digital resources. Getting started
2025-07-01T00:00:00
2025/07/01
https://blog.cloudflare.com/introducing-pay-per-crawl/
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How Minimum Wages and Taxes Can Combat Income Inequality
How Minimum Wages and Taxes Can Combat Income Inequality
https://knowledge.wharton.upenn.edu
[]
“We hope that AI will be complimentary, although in some sense, it's also replacing some work functions,” Salgado said. How the Minimum Wage ...
Wage inequality in the U.S. has increased substantially over the past 70 years, but the manner in which policymakers have used two familiar devices to redistribute wealth and narrow the gap — minimum wages and taxes — has changed considerably, according to a new Wharton research paper. Workers, on their part, try to better their lot by upgrading their technical skills, but the wage gap between skilled and unskilled workers widens, worsening inequality, the paper noted. Under perfect market conditions, the ideal way to reduce income inequality is to use minimum wages and income taxes in a complementary way instead of one substituting the other, according to the paper, titled “Are Minimum Wages and Income Taxes Complements or Substitutes in Addressing Rising Skill Premia?” In such redistribution, taxes collected from higher-skilled and higher-income workers are used to benefit lower-skilled and lower-income workers with higher minimum wages, welfare programs, or direct cash transfers. The paper’s authors, Wharton finance professor Sergio Salgado and Indian School of Business economics and public policy professor Shiv Dixit, provide a framework to use those redistributive tools optimally, adjusting for changes in skill levels and the government’s ability to audit individual tax filings. The authors noted that although minimum wage limits and redistributive income taxes have the “shared goal” to reduce income inequality, there is no consistency in how U.S. states use them. Some states treat them as complements or use them together, while others treat them as substitutes, where they pick one in place of the other; the variation also shows up across different time periods. In addition to empirical facts, the main finding of the paper is the heterogeneity in how states use the two levers differently. The model attempts to explain that heterogeneity, and to explain under which conditions policymakers could combat increasing income inequality using either minimum wages or taxes, and whether they should use them together or separately. The authors chose state taxes (instead of federal taxes) because of the variations in how states use the two tools. The paper showed that differences in the sensitivity of the auditing technology — that is, the ability of the tax authorities to verify whether individuals are correctly reporting their income — to changes in income can explain variations in minimum wages and income taxes across states and over time. “The choice of instruments a planner might use depends on how good you are as a country or as a state in auditing your workers to check whether or not they are telling the truth about their income,” said Salgado. “If you have good auditing technology, using taxes is a good idea because you can go and check if workers have enough money, and redistribute accordingly. But if you don’t have a good auditing technology where it is easy for workers to hide their income, maybe it’s better to use minimum income for redistribution.” “The choice of instruments a planner might use depends on how good you are as a country or as a state in auditing your workers to check whether or not they are telling the truth about their income.”— Sergio Salgado Investigating what causes those different approaches and the resulting different outcomes guided the authors to the crux of the paper: What determines the optimal mix of wage floors and taxes in the face of rising skill inequality? Using U.S. government data on wage floors and income taxes from 2000 to 2015, they modeled their exercise to understand how public policies respond to changes in workers’ skill levels, termed as skill-biased technical change (SBTC). Why Audits and Skill Premiums Matter The study found that designing the optimal policy mix of minimum wages and income taxes depends on the government’s wherewithal to verify that workers disclose their wages and technical skills that impact productivity. The paper noted that intuitively, the minimum wage serves as an indirect mechanism for extracting firm profits and redistributing them to low-skilled workers, assuming that firm profits are not directly taxed. When high-skilled workers upgrade their skills and raise their “skill premium,” the resulting increase in high-skilled wages expands the income tax base, leading to higher tax revenues and larger transfers to low-skilled workers. When low-skilled workers receive more generous transfers, the relative importance of their labor earnings diminishes, making job losses or reduced hours less costly in welfare terms, the paper noted. But without effective audits of workers’ productivity with skill upgrades, the case weakens for using minimum wages and taxes as complementary tools; that relationship can shift from complementarity to substitutability, the paper argued. The paper identified two main factors that drive tax evasion. One, the IRS typically audits higher-income individuals — about a seventh of the filings by individuals earning in the seven digits are audited, compared to the overall rate of 0.62%. Two, when public policies reduce disposable income — through lower minimum wages or higher tax rates — evasion is more attractive, leading individuals to underreport more of their income. “As aggregate evasion rises while enforcement capacity remains fixed, detection probabilities decline,” the authors noted. How Skill Premiums Influence Income Inequality With skill-biased technical change, the wages of high-skilled workers in the study sample increased faster than those of lower-skilled workers, increasing income inequality between the two. “Changes in technology over time have benefited people who have used or know how to use information technology,” Salgado said. “Low-income workers might not have been able to use such technology because it is not complementary to them. That, in part, explains the increase in inequality.” Salgado pointed to two sources of technology that influence the skill premium for workers. One source is technology that complements the skill sets that high-skill workers already have, such as knowledge of how to use computers or other technologies. The other is technology that could replace the manual work that low-skilled individuals could do. “The minimum wage serves a dual purpose — not only does it redistribute income, but it can also discourage high-skilled individuals from pretending to be low-skilled to receive benefits intended for the latter.”— Shiv Dixit Automation and outsourcing tend to keep the wages of low-income individuals very flat, but computers, the internet, and AI tend to complement workers’ existing skills. “We hope that AI will be complimentary, although in some sense, it’s also replacing some work functions,” Salgado said. How the Minimum Wage Serves a Dual Purpose If the government can ascertain through audits what workers declare about their earnings and therefore their skill levels, and new technologies mainly benefit high-skilled workers, then it makes sense to raise both taxes and the minimum wage. “When the government knows exactly how productive each worker is, a rise in the skill premium increases the case for using taxes to redistribute income,” said Dixit. As high-skilled workers earn more, they pay more in income taxes, which allows the government to provide larger transfers to low-skilled workers, he explained. Higher minimum wages could lead to job cuts or reduced hours for workers — those transfers help offset the resulting income loss, he added. “When low-income individuals receive higher transfers, the overall welfare loss from job cuts is smaller,” Dixit continued. “As a result, policymakers may be more willing to raise the minimum wage even if it reduces some low-skilled employment, because the affected workers are better protected.” Higher minimum wages can also help in preventing workers from underreporting their earnings or skill levels, when the government doesn’t have the auditing resources to ascertain their skill levels. “In such cases, the minimum wage serves a dual purpose — not only does it redistribute income, but it can also discourage high-skilled individuals from pretending to be low-skilled to receive benefits intended for the latter,” Dixit said. By setting the minimum wage high enough, the government can limit the consumption of low-skilled workers, who might be unemployed or underemployed as a result. That would make it unattractive for high-skilled workers to misrepresent themselves as low-skilled to claim benefits, Dixit explained. “In this way, the minimum wage becomes a screening tool to preserve the integrity of redistributive programs.” Salgado said their paper contributes to the debate on how to decrease income inequality or how to go about redistribution of wealth. “The question is how we should address the issue, especially for those who may not have a living wage or live paycheck to paycheck.” According to Salgado, their paper is relevant now in light of the current administration’s efforts to cut taxes on rich individuals. “That will increase income inequality for sure,” he said. Reducing the power of the IRS to audit individuals could also indirectly increase income inequality, he added.
2022-12-01T00:00:00
https://knowledge.wharton.upenn.edu/article/how-minimum-wages-and-taxes-can-combat-income-inequality/
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What Workers Really Want from Artificial Intelligence | Stanford HAI
What Workers Really Want from Artificial Intelligence
https://hai.stanford.edu
[ "Shana Lynch" ]
1 day ago · ...
Artificial intelligence is radically shifting the labor market. Today’s workers are increasingly turning to AI for everyday tasks, while automation is reshaping entire sectors of the economy and companies from Amazon to Microsoft are announcing workforce reductions driven by AI deployment. But the narrative in earning calls and news articles leaves critical questions unanswered: What do workers want from AI, and does the technology’s capabilities align with those desires? To answer these questions, researchers from the Stanford Institute for Human-Centered AI and the Digital Economy Lab undertook a comprehensive study of U.S. workers and AI experts. They surveyed 1,500 workers to discern where AI agents could benefit work and where they might cause harm and interviewed 52 AI experts to better understand the technology’s current abilities. The researchers then plotted worker desires alongside AI capabilities to identify opportunities and tasks that warrant reconsideration for automation. The preprint study concluded that workers seek automation primarily for repetitive tasks but prefer to retain agency and oversight over these AI tools. Alarmingly, it also revealed a significant disconnect between what employees desire from AI and the reality of its current capabilities. The findings also suggest a shift in the type of work that earns higher wages: Salaries for traditional information analysis will likely dip, while interpersonal skills and emotional intelligence will earn more. “As the workforce evolves, understanding and bridging the gap between worker expectations and the realities of AI capabilities will be crucial for organizations striving for successful integration,” said co-author Diyi Yang, a Stanford assistant professor of computer science and affiliate of Stanford HAI. “This report offers a timely and structured baseline of where we are right now.” What People Want The scholars surveyed 1,500 individuals in 104 occupations to understand where workers desire automation and where they resist it. Trust emerged as a top concern: 45% expressed doubts about the accuracy and reliability of AI systems, while 23% feared job loss and 16% worried about the lack of human oversight. Many respondents were especially concerned about AI encroaching on creative tasks or handling communication with vendors and clients. Conversely, they welcomed automation that would free up time for higher-value work (69.4%), reduce task repetitiveness (46.6%), and improve the quality of their work (46.6%). Specifically, they welcomed automation that might include scheduling client appointments, maintaining files of information, or rectifying errors in records. The study also explored preferences regarding the level of AI involvement. Most respondents favored a collaborative approach, with 45.2% desiring an equal partnership between workers and AI and 35.6% seeking human oversight at critical junctures. This indicates a clear resistance to fully automated systems, the scholars noted.
2022-12-01T00:00:00
https://hai.stanford.edu/news/what-workers-really-want-from-artificial-intelligence
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Will AI skyrocket inequality? - by Brian Albrecht - Economic Forces
Will AI skyrocket inequality?
https://www.economicforces.xyz
[ "Brian Albrecht" ]
But there are a ton of interesting questions, major questions, around labor markets and AI. How much will relative wages adjust? Which workers ...
There are some absolutely crazy predictions around AI. Recently, the head of Ford said “Artificial intelligence is going to replace literally half of all white-collar workers in the U.S.” There’s literally no plausible, data-relevant definition of “white-collar workers” where that would happen. Wages will adjust. People will adapt. But there are a ton of interesting questions, major questions, around labor markets and AI. How much will relative wages adjust? Which workers will benefit and which will lose out? Today, I want to narrow it down even more: Will AI increase inequality? Spoiler alert, but I don’t know. However, I think price theory gives us a framework to start thinking through it. And that framework points in some new directions. The beauty of approaching AI this way isn’t that we get a perfect crystal ball. It’s that we get a systematic way to organize our thinking about which effects matter most and in what direction. Instead of getting lost in the details of which specific jobs AI might automate, we can focus on the big economic forces that actually drive wage patterns. That’s what price theory is for. The Katz-Murphy Framework: Supply and Demand for Skill Forget the sci-fi scenarios and go back to the basics. Supply and demand for different types of workers. Specifically, the framework that Larry Katz and Kevin Murphy gave us in 1992—a simple model that’s been quietly explaining wage inequality for over thirty years. The setup is almost embarrassingly simple. Take the entire U.S. workforce and divide it into two groups: “skilled” workers and “unskilled” workers. That’s it. No detailed task categories, no industry-specific analysis, just two big buckets. Empirically, we can think of skilled as college grads and unskilled as everyone else. (We will come back to this in the AI context in a bit.) These two types of workers aren’t perfect substitutes—you can’t just swap a college grad for a high school grad at a 1:1 ratio and get the same output. Firms can adjust their mix of workers based on relative wages and productivity. The elasticity of substitution captures how easily firms can substitute between the two groups. KM estimate this at around 1.4, meaning if skilled workers become 10% more expensive relative to unskilled workers, firms will shift toward using about 14-16% fewer skilled workers relative to unskilled workers. On the demand side, there’s another aspect to think about; suppose technology systematically favors skilled workers. This is the famous “skill-biased technical change.” Each year, new technologies (computers, software, automation) tend to complement high-skill workers (making them more productive) while substituting for low-skill workers (automating their tasks). In the KM model, this shows up as a steady outward shift in relative demand for skilled workers. Historically, they estimate the demand shift has been remarkably constant at about 2-3% per year since 1960. Think of it this way: every year, technology effectively creates the equivalent of 2-3% more demand for college graduates relative to high school graduates. If the supply of college graduates grows at exactly that rate, wage inequality stays constant. If supply grows faster, inequality falls. If supply grows slower, inequality rises. It’s that simple. So that’s what workers produce for firms. That’s the demand side for abor. The supply side is driven by educational choices. When the returns to college are high, more people invest in education, increasing the supply of skilled workers. But there’s a lag; it takes years for educational investments to show up in the workforce, and the stock of human capital changes slowly as older, less-educated workers retire and younger, more-educated workers enter. Here’s why this framework has been so powerful: it correctly predicted the major twists in U.S. wage inequality over six decades. In the 1970s, the baby boomers flooded into the workforce with college degrees, causing the supply of skilled workers to surge faster than demand. Result? The college wage premium actually fell during the 1970s—exactly what the model predicted. Then in the 1980s, the growth in college graduates slowed just as computerization accelerated the demand for skilled workers. Result? Skyrocketing inequality—again, exactly what the model predicted. The updated evidence through 2020 is remarkable. Using the same 2.5% annual demand growth trend estimated on 1963-1987 data, the model continues to track actual wage patterns thirty-three years out of sample. How well? Let me answer in a roundabout way. Acemoglu and Autor have a handbook chapter on “Skills, Tasks and Technologies.” The whole point of the chapter is to argue for a new paradigm for modeling labor economics beyond the canonical, KM-model. They are setting up KM to knock it down. And they show how the model predicts out of sample. The authors say, “The model systematically deviates from the data thereafter (1987), predicting a sharper rise in the college premium than actually occurs. While the observed college premium rose by 12 points between 1992 and 2008, the model predicts a rise of 25 log points.” Fair. If you collapse the model down to the particular point estimate made in the original paper, that is correct. I’d say a model is more general than that. But still, my takeaway is different. Look what you get with two parameters! It perfectly tracked for another 15 years. On one of the biggest questions in labor economics! That’s the power of a simple, well-constructed model. So how does AI fit into this framework? Some people will say it changes everything. Something something, self-replicating, something. P(DOOM). Or maybe it’s just P(economy goes boom). Instead, I think we want to think through how AI will influence the parameters and what that means going forward. I’m fine saying that the parameters will change. Technology will change differently than it did from 1963-1987. But how? We still have the same basic structure of supply and demand for skilled versus unskilled workers, but AI fiddles with both dials simultaneously. We don’t have to rely purely on theory here. Eloundou, Manning, Mishkin, and Rock had a great early study looking at GPTs. So we are trying to extrapolate from GPTs to AI as a broader category. It’s not perfect. It’s a bit dated in this space at this point (2023). But it’s a start. The researchers evaluated every major occupation in the U.S. economy, measuring what fraction of each job’s tasks could be significantly sped up by GPTs. First, just some general numbers: 80% of workers have at least 10% task exposure, while 19% have at least 50% task exposure when accounting for complementary technologies. That’s just exposure, not necessarily adoption, but this is from the vantage point of 2023 already. Evidence for Higher γ: The Wage-Exposure Correlation Higher-wage occupations show systematically higher GPT exposure. This is the exact opposite of traditional automation patterns, where technology typically displaced lower-wage workers first. The study finds that occupations requiring bachelor’s, master’s, and professional degrees show much higher exposure than those requiring only high school education. When they regress exposure on skill importance, programming and writing skills are strongly positively correlated with GPT exposure, while routine manual tasks show negative correlations. This is precisely the signature of an acceleration in skill-biased technical change. If we translate their exposure measures into productivity impacts, we’re looking at technology that could boost the effective productivity of college-educated workers by 10-50% while leaving high school educated workers largely unaffected. In KM terms, that’s a massive positive shock to the relative demand for skilled workers. So far, so obvious—this would increase inequality. But what if “exposure” means that GPTs can do your job? Think about tasks that used to require a college degree: writing reports, analyzing spreadsheets, basic coding, document review. AI can now help high school graduates do many of these tasks competently. In the language of task-based models, AI is yanking cognitive-routine work out of the “skilled” bucket and creating new “unskilled + AI” hybrid categories. Translated back into KM terms, purely in the model, you might think this looks like an effective surge in the supply of skilled workers even if the actual number of college graduates doesn’t change. Suddenly you have more people who can do “skilled” work (with AI assistance), which should put downward pressure on wage premiums. But go back to the data. This would be an increase in the relative demand for people who are labeled as unskilled labor, even if now they are “skilled” in some other sense. This is the real horse race. Unfortunately, the Katz-Murphy model doesn’t really help us pin down this parameter ex ante. We need to see how it plays out. Evidence for Higher σ: Task Reallocation Patterns The GPT study also provides indirect evidence for increased substitutability between skill levels. The researchers distinguish between tasks that GPTs can handle directly versus those requiring complementary software. The key insight: many “high-skill” tasks that previously required specialized training—legal research, financial analysis, code review—now show high direct exposure. Meanwhile, other high-skill tasks requiring scientific reasoning or critical thinking show low exposure. I’d think of this kind of task reshuffling as a force that increases substitutability. Suddenly, a senior analyst can handle document review that previously required a junior lawyer. An experienced programmer can tackle financial modeling that once needed a specialist. The boundaries between skill categories become more fluid. A higher σ—that is, greater substitutability between college and non-college workers—does three things to wage inequality over time: First, it flattens the wage-premium response to any demand shock. In the old KM calibration (σ ≈ 1.4), a one-shot 10% demand jump for college labor shows up as roughly a 7% wage-premium spike. Bump σ to 2 and the same demand shock translates into maybe 5%. Wages move less for a given quantity shock Second, it makes supply shifts bite harder. When σ is low, pumping more B.A.’s into the workforce barely dents the premium; when σ is high, the same graduation boom can cut the gap in half. Translation: policy levers like immigration or community-college completion become more potent equalizers in a high-σ world. Third, it makes the wage series more volatile. Flatten the demand schedule and you magnify the impact of every supply wobble—graduation cohort sizes, business-cycle layoffs, even AI-augmented up-skilling inside firms. Expect a rockier premium path: smaller but more frequent zig-zags instead of one long climb. Bottom line: a bigger σ doesn’t cancel AI-driven inequality, but it does hand supply-side forces more power and compresses the amplitude of each pure demand shock. Overall effects My best guess? I don’t know. But I’ll say we’ll see bifurcated effects. At the top of the skill distribution, AI will act like turbo-charged technical change, where supercharged means maybe 1% more for 1 decade, not utopia-type stuff. This ends up creating huge demand for people who can work effectively with AI systems. This will drive inequality between the college-educated and everyone else. But within the college-educated group, AI might compress inequality by making routine cognitive work more accessible to workers with less specialized training. The real question isn’t whether AI will change inequality—it will. The question is in which direction and by how much. Maybe we should split the labor market into more than two groups. Autor and Acemoglu think so. Still., the Katz-Murphy framework gives us a way to think systematically about the forces at play. But as with any good economic model, the devil is in the parameters. And those parameters are changing in real time.
2022-12-01T00:00:00
https://www.economicforces.xyz/p/will-ai-skyrocket-inequality
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CrowdGen by Appen – Get paid to train AI
CrowdGen by Appen
https://crowdgen.com
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Earn remotely by completing online tasks that help improve AI. Work at your preferred time and gain real-world, hands-on experience in training AI.
AI has the power to solve some of the world’s biggest challenges, when developed and deployed ethically, responsibly, and with everyone’s benefit in mind. Be part of our global, diverse community of 1M+ contributors and help us create AI that is relevant, trustworthy, and truthful. Your work ensures that voices of people from different places, backgrounds, and beliefs are represented in AI models, contributing to a more equitable world.
2022-12-01T00:00:00
https://crowdgen.com/
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Pave: Compensation Management Software
Compensation Management Software
https://www.pave.com
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Benchmark compensation, price jobs, manage pay ranges, run merit cycles, and ...
Markets go up and down, but the competition for talent never rests. That's why our in-house compensation experts, data science team, and extensive partner network are always working hard to bring you compelling insights.
2022-12-01T00:00:00
https://www.pave.com/
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Outlier AI: Train the Next Generation of AI as a Freelancer
Train the Next Generation of AI as a Freelancer
https://outlier.ai
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What is Outlier? A platform for building AI with expert human input. Discover Outlier AI, join a community for freelancers, and shape the next generation of ...
What qualifications do I need? Candidates should have deep expertise in the domains of focus that they are applying for. Our job descriptions will have more specific details on what would be expected in each domain, but we encourage you to submit your application. Minimum qualifications are usually junior and seniors in undergraduate programs of the domain. Preferred qualifications are graduate students, masters, and PhD holders of the domain. We also expect all candidates to have a strong understanding of written English and clear communication skills. Passion and commitment to be part of an exciting journey to help build the next generation of Generative AIs.
2022-12-01T00:00:00
https://outlier.ai/
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Work Remotely as an AI Trainer | Pareto.AI
Work Remotely as an AI Trainer
https://pareto.ai
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Earn industry-leading pay while contributing to cutting-edge AI development as an AI trainer with Pareto.AI.
Pareto is committed to maintaining a respectful, ethical workplace. Our remote environment allows everyone, including our staff, to work in the comfort of their home. Beyond our community structure, we refuse to permit harassment and discrimination in any form. Finally, we abhor any system which disenfranchises its labelers. For more information, please read our Code of Conduct and Modern Slavery Statement.
2022-12-01T00:00:00
https://pareto.ai/careers/ai-trainer
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Azure AI Document Intelligence pricing
Pricing - Azure AI Document Intelligence
https://azure.microsoft.com
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Pricing details for Document Intelligence, a text and data extraction API from Azure AI Services. Pay for the plan that best fits your needs.
Prices are estimates only and are not intended as actual price quotes. Actual pricing may vary depending on the type of agreement entered with Microsoft, date of purchase, and the currency exchange rate. Prices are calculated based on US dollars and converted using London closing spot rates that are captured in the two business days prior to the last business day of the previous month end. If the two business days prior to the end of the month fall on a bank holiday in major markets, the rate setting day is generally the day immediately preceding the two business days. This rate applies to all transactions during the upcoming month. Sign in to the Azure pricing calculator to see pricing based on your current program/offer with Microsoft. Contact an Azure sales specialist for more information on pricing or to request a price quote. See frequently asked questions about Azure pricing.
2022-12-01T00:00:00
https://azure.microsoft.com/en-us/pricing/details/ai-document-intelligence/
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Mindrift.ai: Be the “I” in AI
Mindrift.ai: Be the “I” in AI
https://mindrift.ai
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Turn your expertise into paid AI training contributions. No technical AI expertise needed ...
That depends on client demand and your area of expertise. For example, English editors may be invited more often than niche roles like automotive engineers. Joining the talent pool increases your chances of being invited.
2022-12-01T00:00:00
https://mindrift.ai/
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Minimum Wage Rate in the US by State (2025) | Paycom Blog
Minimum Wage Rate in the US by State (2025)
https://www.paycom.com
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AI Standards · Implementation · Dedicated Service · Security · Automation ...
This is a state minimum wage update and does not cover any updates to specific local, municipal or industry minimum wages or rates for contractors or tipped workers. Please consult legal counsel for guidance on how to stay compliant with all the minimum wage laws where your business operates. Minimum wages can change periodically, depending on various state and federal laws. While some states follow federal guidance, others set their own requirements. Understanding the rules affecting the state(s) you operate in is key to compliance. What is the federal minimum wage? The current federal minimum wage is $7.25 per hour. States with their own hourly wage requirements may exceed this rate, but employers specifically covered by the Fair Labor Standards Act (FLSA) must adhere to the federal minimum wage. What legislation established the federal minimum wage? President Franklin D. Roosevelt signed the FLSA into law in 1938. At the time, the law placed the minimum wage at just 25 cents per hour. The law also created standards for child labor and overtime pay. How often does the federal minimum wage rise? While the FLSA is an evolving document, it doesn’t automatically increase the minimum wage. For example, the current rate was enacted in 2009 — almost 15 years ago. The president must sign any change to the federal minimum wage into law. But that doesn’t stop certain states from forming their own standards. What is the minimum wage in each state for 2025? Don’t get blindsided by an unexpected compliance change. To make it easier to identify updates, we’ve provided a list of 2025 and 2024’s hourly minimum wages by state. Keep in mind this list doesn’t consider every city or municipality with its own minimum wage requirement. Understand these hourly minimum wage rates for any of the states where your business operates: State 2025 Minimum Hourly Wage 2024 Minimum Hourly Wage Alabama $7.25 $7.25 Alaska $13.00* $11.73 Arizona $14.70* $14.35 Arkansas $11.00 $11.00 California $16.50 $16.00 Colorado $14.81* $14.42 Connecticut $16.35* $15.69 Delaware $15.00 $13.25 Florida $13.00* $13.00 Georgia $7.25 $7.25 Hawaii $14.00 $14.00 Idaho $7.25 $7.25 Illinois $15.00 $14.00 Indiana $7.25 $7.25 Iowa $7.25 $7.25 Kansas $7.25 $7.25 Kentucky $7.25 $7.25 Louisiana $7.25 $7.25 Maine $14.65* $14.15 Maryland $15.00 $15.00 Massachusetts $15.00 $15.00 Michigan $12.48 $10.33 Minnesota $11.13* $8.85 for small employers and $10.85 for large employers.‡ Mississippi $7.25 $7.25 Missouri $13.75* $12.30 Montana $10.55*¶ $10.30 Nebraska $13.50* $12.00 Nevada $12.00* $12.00 New Hampshire $7.25 $7.25 New Jersey $15.49 for most employers; $14.53 for seasonal and small employers who have less than six workers.* $15.13 for most employers; $13.73 for seasonal and small employers who have less than six workers. New Mexico $12.00 $12.00 New York $16.50 for New York City, Long Island and Westchester County; $15.50 for the rest of the state.* $16.00 for New York City, Long Island and Westchester; $15.00 for the rest of the state. North Carolina $7.25 $7.25 North Dakota $7.25 $7.25 Ohio $10.70 for employers with annual gross receipts of $394,000 or more. $10.70 per hour for nontipped employees and $5.35 per hour for tipped employees.* $10.45 for employers with annual gross receipts of $385,000 or more. Minimum wage of $7.50 for employers with annual gross receipts under $385,000. Oklahoma $7.25 $7.25 Oregon Basic minimum wage is $15.05, $16.30 for Portland Metro Area and $14.05 for nonurban counties.* Basic minimum wage is $14.70, $15.95 for Portland Metro Area and $13.70 for nonurban counties. Pennsylvania $7.25 $7.25 Rhode Island $15.00 $14.00 South Carolina $7.25 $7.25 South Dakota $11.50* $11.20 Tennessee $7.25 $7.25 Texas $7.25 $7.25 Utah $7.25 $7.25 Vermont $14.01* $13.67 Virginia $12.41* $12.00 Washington, D.C. $17.95* $17.50 Washington $16.66* $16.28 West Virginia $8.75 $8.75 Wisconsin $7.25 $7.25 Wyoming $7.25 $7.25 * Minimum wage is adjusted annually based on the Consumer Price Index. ‡ Minnesota defines “large employers” as businesses with $500K or more in gross revenue. ¶ A business not covered by the federal Fair Labor Standards Act whose gross annual sales are $110,000 or less may pay $4 per hour. However, if an individual employee is producing or moving goods between states or otherwise covered by the federal Fair Labor Standards Act, that employee must be paid the greater of either the federal minimum wage or Montana’s minimum wage. Download our 2025 State Minimum Wage Guide Which states are increasing their minimum wage in 2025? Twenty-two states are experiencing a minimum wage increase in 2025, including: Alaska Arizona California Colorado Connecticut Delaware Illinois Maine Michigan Minnesota Missouri Montana Nebraska New Jersey New York Ohio Oregon Rhode Island South Dakota Vermont Virginia Washington California fast-food minimum wage Fast-food workers in California are covered under a minimum wage requirement of $20 per hour. This wage increase applies only to employers with 60 or more establishments nationwide. This means that even franchises with a small presence in California will still need to comply. The California Fast Food Council has the authority to raise the fast-food minimum wage effective Jan. 1, 2025, but so far has not acted to do so. Washington, D.C. minimum wage The minimum wage for Washington, D.C., is $17.95, effective July 1, 2025. Which state has the lowest minimum wage? Georgia and Wyoming’s hourly minimum wage are tied at $5.15. However, employers covered by the FLSA must adhere to the federal requirement of $7.25. Which state has the highest minimum wage? While Washington is technically the state with the highest hourly minimum wage at $16.66, Washington, D.C. has the highest rate across the country: $17.50! Which states have minimum wages of $15.00 or more? Eleven states and Washington, D.C. have minimum wages of $15.00 or more: California Connecticut Delaware Illinois Maryland Massachusetts New Jersey New York Oregon Rhode Island Washington What is the new minimum wage for federal contractors? On Jan. 1, 2025, Executive Order 14026 will raise the minimum wage rate for federal contractors to $17.75 per hour, according to the DOL notice published on Sept. 30, 2024. State minimum wage compliance assistance To ensure compliance and avoid penalties, employers must understand and comply with both federal and state minimum wage laws. Paycom’s time and labor management tools help you capture employees’ hours worked, optimize scheduling, track labor dollars, automate time-off request approvals and more. Our minimum wage warning feature alerts you if an employee is earning less than the minimum wage and displays the amount needed to bring the employee’s pay up to compliance. Our single software also monitors legislative changes that would affect overtime state by state and updates accordingly to help keep you in compliance, no matter your head count or locations. Minimum EAP salary requirements The U.S. Department of Labor’s regulations require executive, administrative and professional (EAP) employees to be paid at least: $844 per week ($43,888 per year) effective July 1, 2024 $1,128 per week ($58,656 per year) beginning on Jan. 1, 2025 FAQ What is the minimum wage for tipped employees? The minimum wage for tipped employees varies by state. What are some minimum wage exemptions? Some minimum wage exceptions apply under specific circumstances to workers with disabilities, full-time students, youth under age 20 in their first 90 consecutive calendar days of employment, tipped employees and student learners. How often does the federal minimum wage increase? The federal minimum wage last increased in 2009. To whom does the minimum wage apply? The minimum wage applies to covered nonexempt workers in the private sector and in federal, state and local governments. What is the difference between state minimum wage and federal minimum wage? If a state’s minimum wage is less than the federal minimum wage of $7.25, employers must pay the federal rate. If the state minimum wage is more than the federal, employers must pay the state rate. Adhering to federal and state minimum hourly wage guidance helps you remain compliant and ensures your success. And a powerful government and compliance tool helps you stay on top of new laws and regulations that affect your business. Download our 2025 HR and Payroll Calendar for easy access to the dates all HR and payroll managers should know and subscribe to our newsletter to stay up to date with federal legislation.
2022-12-01T00:00:00
https://www.paycom.com/resources/blog/minimum-wage-rate-by-state/
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Meta Pay
Meta Pay
https://www.meta.com
[]
Apps. Facebook · Messenger · Instagram · WhatsApp · Meta Horizon ; Services. Meta AI · AI Studio · Llama · Meta Pay ; Community. About Meta · Businesses.
Meta Pay is an easy, secure way to pay on the apps you already use. Not in the US? Check availability
2022-12-01T00:00:00
https://www.meta.com/meta-pay/?srsltid=AfmBOorDikLY5Xclocwd87z5AOd99TTx_m_syR5-0Hfk4V__e9zBdjyU
[ { "date": "2022/12/01", "position": 99, "query": "AI wages" } ]
aiEDU
aiEDU
https://www.aiedu.org
[]
aiEDU is a 501(c)(3) non-profit that is devoted to ensuring all students are ready to live, work, and thrive in a world where AI is everywhere.
We’re preparing students to thrive in a world where AI is everywhere. We envision a world where our education system evolves to better meet the new demands of a world transformed by AI. This requires a national effort to bring together education partners, school systems, and other stakeholders in the K12 ecosystem to work collaboratively toward a clear, shared goal.
2022-12-01T00:00:00
https://www.aiedu.org/
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AI for Education
AI for Education
https://www.aiforeducation.io
[]
We partner with schools and districts around the world to lead high quality PD and training to drive the responsible adoption of Generative AI.
Subscribe today to get the latest free resources, tools, and news on how to bring AI into your school and practice.
2022-12-01T00:00:00
https://www.aiforeducation.io/
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AI for Educators | MagicSchool
AI for Educators
https://www.magicschool.ai
[]
The magic of AI to help schools with presentations.|. The most loved, secure, and trusted AI platform for educators and students. Teachers sign up free.
AI for schools loved by over 5 million educators We are the award-winning, most used, and most loved AI for educators in the world - now in nearly every U.S. school district and in 160 countries around the world. MagicSchool is built for educators, by educators, providing a genuine opportunity to reclaim valuable time for educators, combat burnout, and elevate the art of teaching.
2022-12-01T00:00:00
https://www.magicschool.ai/
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Advancing Education Using Google AI
Advancing Education Using Google AI
https://edu.google.com
[]
AI can help educators boost their creativity and productivity, giving them time back to invest in themselves and their students.
Google Workspace for Education is built on our secure, reliable, industry-leading technology infrastructure. Users get the same level of security that Google uses to protect our own services, which are trusted by over a billion users around the world every day. While AI capabilities introduce new ways of interacting with our tools, our overarching privacy policies and practices help keep users and organizations in control of their data. In addition, all core Workspace tools – like Gmail, Google Calendar, and Classroom – meet rigorous local, national, and international compliance standards, including GDPR, FERPA, and COPPA. Chromebooks are designed with multiple layers of security to keep them safe from viruses and malware without any additional software required. Each time a Chromebook powers on, security is checked. And because they can be managed centrally, Chromebooks make it easy for school IT administrators to configure policies and settings, like enabling safe browsing or blocking malicious sites.
2022-12-01T00:00:00
https://edu.google.com/intl/ALL_us/ai/education/
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Artificial Intelligence in Education - ISTE
Artificial Intelligence in Education
https://iste.org
[]
ISTE offers free resources and guides for educators who are interested in learning about how artificial intelligence can empower learners at every level.
AI Lessons Educators can strengthen students' AI literacy through various hands-on activities, ranging from technology-free "unplugged" exercises to the development of chatbots and simple video games. The curriculum includes specialized guides tailored for different teaching contexts - elementary school, secondary school, elective courses, and computer science classes - along with a dedicated guide focusing on AI ethics. These educational resources are available for download in English, Spanish, and Arabic.
2022-12-01T00:00:00
https://iste.org/ai
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AI-for-Education.org: Home
AI-for-Education.org
https://ai-for-education.org
[]
A community to ensure equitable access and benefits from AI in Education. Our vision is to ensure equitable access to AI's potential to improve learning.
Our vision is to ensure equitable access to AI’s potential to improve learning, making it accessible to all children and teachers, irrespective of their socio-economic status. We bring together educators, policymakers and developers to guide the development of AI educational tools for low- and middle-income countries (LMICs). This is a space where educational technology, AI insights, and developmental experiences are shared. We believe it is better to build together rather than separately.
2024-01-10T00:00:00
2024/01/10
https://ai-for-education.org/
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Eduaide.Ai: AI Created for Teachers
Eduaide.Ai: AI Created for Teachers
https://www.eduaide.ai
[]
Maximize your impact with Eduaide—an AI-powered workspace designed for teachers to simplify lesson planning, resource creation, and feedback.
There are many AI tools for teachers, but Eduaide is one of my favorites because of its variety of subject-specific tools and levels of customization... Whether you are curious about AI, or an experienced user, I highly recommend Eduaide! Karle Delo
2022-12-01T00:00:00
https://www.eduaide.ai/
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Generative AI for Educators - Grow with Google
Generative AI for Educators
https://grow.google
[ "Secretary Sanders", "Jose Dotres", "Michael Matsuda" ]
Learn AI skills with Google Generative AI for Educators. Save time, personalize instruction, and enhance lessons, no previous experience required.
Generative AI for Educators is a two-hour, self-paced course designed to help teachers save time on everyday tasks, personalize instruction to meet student needs, and enhance lessons and activities in creative ways with generative AI tools — no previous experience required. Developed by experts at Google in collaboration with MIT RAISE (Responsible AI for Social Empowerment and Education), this no cost course is built for teachers across disciplines and provides practical, hands-on experience. After completing the course, teachers earn a certificate from the course, which they can present to their district for professional development (PD) credit, depending on district and state requirements.
2022-12-01T00:00:00
https://grow.google/ai-for-educators/
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Microsoft 365 AI Education Tools
Microsoft 365 AI Education Tools
https://www.microsoft.com
[]
Explore AI tools in the classroom with Microsoft Education. See how you can use AI to personalize learning experiences, and empower students and educators ...
Microsoft believes that when you create technologies that can change the world, you must also ensure that the technology is trustworthy. We are committed to creating Trustworthy AI by design. Our work is guided by a core set of principles: fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability. We are putting those principles into practice across the company to develop and deploy AI that will have a positive impact on society. We take a cross-company approach through cutting-edge research, best-of-breed engineering systems, and excellence in policy and governance. Learn more about Trustworthy AI here.
2022-12-01T00:00:00
https://www.microsoft.com/en-us/education/ai-in-education
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AI + Education - Stanford Accelerator for Learning
AI + Education • Stanford Accelerator for Learning
http://acceleratelearning.stanford.edu
[]
Overview. From generative AI platforms to adaptive learning programs and more precise feedback, AI is rapidly changing opportunities in teaching and ...
Overview From generative AI platforms to adaptive learning programs and more precise feedback, AI is rapidly changing opportunities in teaching and learning. The use of AI in learning is also sparking challenging questions about what is taught and how and what kind of data needs to be collected. The Stanford Accelerator for Learning is leaning into this space by providing new research, learning, and convening opportunities that bring together talent from across education, science, and technology to chart an ethical, informed, and exciting path for the future. Faculty Lead Victor Lee Associate Professor Research team Catherine Chase Research Director Funding opportunities Generative AI is artificial intelligence that can generate novel content by using existing text, audio files, or images. Generative AI has now reached a tipping point where it can produce high quality output that can support many different kinds of tasks. For example, ChatGPT can write essays and code, DALL-E can create images and art, while other forms of generative AI can produce recipes, music, and videos. These new forms of generative AI have the capacity to change how we think, create, teach, and also learn. The AI+Education program has collaborated with the Stanford Institute for Human-Centered Artificial Intelligence (HAI), to fund two rounds of early and exploratory stages of research on AI and education, including designs, prototypes, and pilot studies that may have the potential to scale or have broad impact in the future. Link to Learn more Learning through Creation with Generative AI The Stanford Accelerator for Learning and the Stanford Institute for Human-Centered Artificial Intelligence (HAI) invited research proposals advancing learning through creation with generative AI. Link to Learn more Generative AI for the Future of Learning In collaboration with the Stanford Institute for Human-Centered Artificial Intelligence, grants up to $100,000 for innovative designs and/or research on critical issues and applications of generative AI in learning contexts.
2022-12-01T00:00:00
http://acceleratelearning.stanford.edu/initiative/digital-learning/ai-and-education/
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AI for educators - Training - Learn Microsoft
AI for educators - Training
https://learn.microsoft.com
[]
Explore the many ways to enhance teaching and learning with AI-powered tools in Microsoft Edge browser, Word, PowerPoint, Minecraft, and more.
Explore the potential of artificial intelligence (AI) in education. It covers a brief history of AI, large language models (LLMs), generative AI, prompt engineering, responsible use of AI, and uses in a class setting. Dive into the art of a prompt to equip learners to get the best results from Microsoft Copilot and Image Creator from Designer. Explore the many ways to enhance teaching and learning with AI-powered tools in Microsoft Edge browser, Word, PowerPoint, Minecraft, and more. ISTE Standards for Educators: Educator - Citizen Educator - Collaborator Educator - Learner UNESCO Standards for Educators: Application of Digital skills Organization and Administration Understanding ICT in Education UNESCO AI Competency Framework:
2022-12-01T00:00:00
https://learn.microsoft.com/en-us/training/paths/ai-education/
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Our Team - AI for Education
Our Team — AI for Education
https://www.aiforeducation.io
[]
Amanda is the Co-Founder and CEO of AI for Education. A former high school biology teacher and EdTech executive with over 20 years of experience in the ...
Amanda is the Co-Founder and CEO of AI for Education. A former high school biology teacher and EdTech executive with over 20 years of experience in the education sector. She has a deep understanding of the challenges and opportunities that AI can offer. She is a frequent consultant, speaker, and writer on the topic of AI in education, leading workshops and professional learning across both K12 and Higher Ed. Amanda is committed to helping schools and teachers maximize their potential through the ethical and equitable adoption of AI.
2022-12-01T00:00:00
https://www.aiforeducation.io/our-team
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Artificial intelligence in education - Wikipedia
Artificial intelligence in education
https://en.wikipedia.org
[]
The field combines elements of generative AI, data-driven decision-making, AI ethics, data-privacy and AI literacy.
Artificial intelligence in education (AIEd) is the involvement of artificial intelligence technology, such as generative AI chatbots, to create a learning environment.[1] The field combines elements of generative AI, data-driven decision-making, AI ethics, data-privacy and AI literacy.[2] Challenges and ethical concerns of using artificial intelligence in education include bad practices, misinformation, and bias.[3] History [ edit ] AIEd can be traced back as early as in the 1960s, when educators and researchers found the developing possibilities of computers in helping to learn. Computer-based instruction systems made use of program instructions for students to experience interactive learning outcomes. One such example is PLATO, which was developed by University of Illinois for the students.[4] In the years 1970s and 1980s, intelligent tutoring systems (ITS) were being adapted to classroom teachings. ITS provided instructions and materials based on performance, representing a customized approach to learning. In November 2022, a chatbot named ChatGPT was released by OpenAI. It rapidly became popular, and its general-purpose capabilities triggered concerns about the potential for cheating. AI content detectors have been developed, although their accuracy was limited. Some schools banned ChatGPT, but many bans were later reverted.[5] Background [ edit ] Artificial intelligence could be defined as "systems which display intelligent behaviour by analysing their environment and taking actions – with some degree of autonomy – to achieve specific goals".[6] These systems might be software-based or embedded in hardware.[7] They can rely on machine learning or rule-based algorithms.[8] There is no single lens with which to understand AI in education (AIEd), but the genealogy of education and AI,[9] its promises and problematics[10] may assist with seeing the bigger picture. The Dartmouth workshop is considered a founding event for AI.[11] At least two paradigms have emerged from this workshop. Firstly the tutoring / transmission paradigm, where AIEd systems represent a conduit for personalizing learning. Secondly, the coordination paradigm, where AIEd is the supporter of a cohort's knowledge construction, and this mass is socialized into new systems of thought. Alternately there is the leadership model, where individuals take agency and make choices about their learning (with or without AI)[12][13] AIEd could be viewed as the ultimate disruption, replacing academics and their scholarly prestige,[14] or an opportunity to consider together, what makes humans different from machines. Emerging perspectives [ edit ] This complex social, cultural, and material assemblage should be seen in its geo-political context. It is likely that AI systems will be shaped by different policy or economic imperatives which will influence the construction, legitimation and use of this assemblage in an education setting.[15][16] Those who see AI as a conduit for knowledge transmission or construction are comfortable with the idea of machine's reasoning or having hallucinations. While those who are sceptics, recognize the cultivated "closed-off imaginative spaces" that big tech has captured, notice how big tech's discourse limits critical thought and discussions about these computational systems.[17] The AI in education community [ edit ] The AI in education community has grown rapidly in the global north, driven by venture capital, big tech, and open educationalists.[18] While some believe AI will improve "access to expertise"[19] and revolutionize learning through natural language processing,[20] others focus on enhancing LLM reasoning.[21][22] In the global south, critics argue that AI's data processing and monitoring reinforce neoliberal approaches to education rather than addressing colonialism and inequality.[23][24] Applications [ edit ] Applications in AIEd can be a wide range of tools that can be used by teacher as well as students for learning outcomes. From primary classrooms to training facilities AI has evolved the way of learning through innovative and engaging delivery techniques.[1] AI based tutoring system [ edit ] Intelligent tutors or Intelligent tutoring systems (ITS) such as SCHOLAR system in the 1970s was use for reciprocal questions being asked between teacher and students. The goal of ITS models was to create an artificial interaction between a student and a teacher.[25] ITS integrated four models the student model which was information about the student's abilities, the teacher model where based on analysis of student's performance strategies and guidance was provided, the domain model (knowledge of students and teacher), the diagnosis model where evaluation was made base on domain model. Although, it improved proficiency in studies, some studies provide negative results and claims of inefficiency than human tutoring were made.[26] ITS is limited, in that, it works better for less-complex learning.[25] ITS have also been used for accessibility purposes, so if teachers have a large number of students they need to attend to, they can use AI to accommodate for students and their differing needs.[25] Custom learning platforms [ edit ] Personalized AI platforms are tailor made for individuals based on their strengths and weakness. The platforms make use of algorithms to predict students patterns and habits based on that they make recommendations to make improvement in their performances. Platforms such as LinkedIn, Duolingo are currently some of the popular companies providing the service. However, there is fair share of criticism as these system based learning platforms might provide isolation and student-teacher interaction may fade. Also, biasness in the train information might lead to misinformation.[27] Automated grading system [ edit ] Automation assessment in grading students helps in saving time for the educator, providing immediate feedback. Systems make use of different rubrics combinations to grade performances. These systems need oversight as there might be scoring biasing.[27] Generative AI [ edit ] AI tools such as Open AI's ChatGPT, and Grok (chatbot) fall under the category of generative AI, they provide results based on interactions and are very good in making use of search algorithms to give precise results to the user. However, there are risk involving over-reliance and violating academic integrity.[28][29] Ethical concerns [ edit ] With the advancement and adoption of AI, there are ethical challenges involved and proactive measure need to addressed to ensure equity and fairness to educators and establishments.[1] Accessibility [ edit ] Equal access to AI could be one of the areas that comes into consideration. As there may many low incomes and rural areas deprived of the platform use. This might widen the gap in terms of education access. Global efforts should be made to accessibility and train educators in those underprivileged areas.[3][30] Bias and fairness [ edit ] AI agents might be trained on biased data according to different company driven agendas. Bias can come in different forms, some of which include: algorithmic, architectural, and machine-learning bias. There are many different kinds of bias that can be introduced to the AI during the machine-learning process.[31] Common types of bias that occur during the machine learning process are: association bias, language bias, exclusion bias, marginalized bias, and sample bias.[32] Since LLMs were created to produce human-like text, bias can easily, and unintentionally be introduced and reproduced.[31] This might lead to knowledge which is fed to them in form of misinformation. There should be policies and check to maintain such bias practices.[30] Data privacy [ edit ] Data privacy is an ethical concern as most of the results are on trained data and it can be misused for various purposes. Additionally, there is a lack of transparency from developers, and compliance laws should make sure of the transparency and data privacy is intact.[25][33] Perspectives [ edit ] Educator Perspectives [ edit ] Educators and school administrations have found AI to be improving the efficiency of work done by a big margin, while some percentage of work force are concerned abut overreliance. Professional development is key to integrating AI effectively to ensue current jobs are not replaced.[34][35] Student Perspectives [ edit ] Students are flexible, with technology such as personalized feedback and self-paced learning, but reliability, privacy, and fairness are concerns.[36][37] Algorithms effects on education [ edit ] AI companies that focus on education, are currently preoccupied with generative artificial intelligence (GAI), although data science and data analytics is another popular educational theme. At present, there is little scientific consensus on what AI is or how to classify and sub-categorize AI[38][39] This has not hampered the growth of AI in education systems, which are gathering data and then optimising models. AI offers scholars and students automatic assessment and feedback, predictions, instant machine translations, on-demand proof-reading and copy editing, intelligent tutoring or virtual assistants.[18] The "generative-AI supply chain",[40] brings conversational coherence to the classroom, and automates the production of content.[41] Using categorisation, summaries and dialogue, AI "intelligence" or "authority" is reinforced through anthropomorphism and the Eliza effect. Framing education [ edit ] Educational technology can be a powerful and effective assistant in a suitable setting. Computer companies are constantly updating their technology products. Some educationalists have suggested that AI might automate procedural knowledge and expertise[42] or even match or surpass human capacities on cognitive tasks. They advocate for the integration of AI across the curriculum and the development of AI Literacy.[43] With higher education facilities finding themselves with an opportunity to create a path for themselves and their students by creating guidelines so that AI can incorporated into their curriculum.[44] Others are more skeptical as AI faces an ethical challenge,[45] where "fabricated responses" or "inaccurate information", politely referred to as "hallucinations"[42] are generated and presented as fact. Some remain curious about societies tendency to put their faith in engineering achievements, and the systems of power and privilege[46] that leads towards deterministic thinking.[47] While others see copyright infringement[48][49][40] or the introduction of harm, division and other social impacts, and advocate resistance to AI.[50] Tokens, text and hallucinations [ edit ] Large language models (LLMs) take text as input data and then generate output text.[51] Coherent sentences are parroted [52] from billions of words and code that has been web-scraped by AI companies or researchers. LLM are often dependent on a huge text corpus that is extracted, sometimes without permission.[53] LLMs are feats of engineering, that see text as tokens. The relationships between the tokens allow LLMs to predict the next word, and then the next, thus generating a meaningful sentence that has an appearance of thought and interactivity. This massive dataset creates a statistical reasoning machine,[54] that does pattern recognition.[55] The LLM examines the relationships between tokens, generates probable outputs in response to a prompt, and completes a defined task, such as translating, editing, or writing. The output that is presented is a smoothed collection of words,[56] that is normalized and predictable. Translation, summarization, information retrieval, conversational interactions are some of the complex language tasks that machines are expected to handle.[57] However, the text corpora that LLMs draw on can be problematic, as outputs will reflect their stereotypes or biases of the people or culture whose content has been digitized.[58] The confident, but incorrect outputs are termed "hallucinations".[59] These plausible errors are not malfunctions but a consequence of the engineering decisions that inform the large language model.[60] "Guardrails" offer to act as validators of the LLM output, prevent these errors, and safeguard accuracy.[61] These metaphorical "hallucinations" contribute towards the misconception that AI is conscious, perhaps AI mirages are a better alternative.[62] There are no fixes[63][64] for AI mirages, the "factually incorrect or nonsensical information that seems plausible".[65] Socio-technical imaginaries [ edit ] The benefits of multilingualism, grammatically correct sentences or statistically probable texts written about any topic or domain are clear to those who can afford software as a service (SaaS). In edtech, there is a recurrent theme, that "emerging technologies"[66] will transform education.[67] Whether it be radio, TV, PC computers, the internet, interactive whiteboards, social media, mobile phones or tablets. New technologies generate a socio technical imaginary (STI) that offer's society, a shared narrative[68] and a collective vision for the future.[69] Improvements in natural language processing and computational linguistics have re-enforced assumptions that underlie this "emerging technology" STI. AI is not an emerging technology, but an "arrival technology"[70] AI appears to understand instructions and can generate human-like responses.[71] Behaving as a companion for many in a lonely and alienated world.[72] While also creating a "jagged technology frontier",[73] where AI is both very good and terribly bad at very similar tasks.[70] Public goods vs venture capital [ edit ] At first glance, artificial intelligence in education offers pertinent technical solutions to address future education needs.[18] AI champions envision a future where machine learning and artificial intelligence might be applied in writing, personalization, feedback or course development. The growing popularity of AI, is especially apparent to many who have invested in higher education in the past decade.[18] Critical skeptics on the other hand, are wary of rhetoric that presents technology as solution. They point out that in public services, like education, human and algorithmic decision systems should be approached with caution.[74] Post digital scholars and sociologists are more cautious about any techno-solutions, and have warned about the dangers of building public systems around alchemy,[74] stochastic parrots or cognitive capitalism.[75] They argue that there are multiple costs that accompany LLMs, including dangerous biases the potential for deception, and environmental costs[52] The AI curious are aware of how cognitive activity has become commodified. They see how education has been transformed into a "knowledge business" where items are traded, bought, or sold.[76] African hyper scalers, venture capital and vice chancellors[77] are punting the Fourth Industrial Revolution, with the prospect of billions earmarked for South African Data centers,[78] such as Teraco Data Environments, Vantage Data Centre,[38] Africa Data Centres[41] NTT /Dimension_Data,[20] carefully avoiding being accused of monopoly practices.[79] AI resilient graduates [ edit ] AI has co-existed comfortably between academia and industry for years.[80] The terrain is shifting and currently AI research in the global north has computing power, large datasets, and highly skilled researchers. Power is shifting away from students and academics toward corporations and venture capitalists.[81] Graduates from universities in dominant cultures, where there are high levels of digitisation, need to become AI-resilient. Graduates from the majority world also need to value their own process of knowledge construction, resist the lure of normalisation and see AI for what it is, another form of enclosure, and start blogging.[opinion] Graduates from both the global north and the majority of the world need to be able to critique AI output, become familiar with the processes of technical change,[82] and let their own studies and intellectual life guide their working futures.[41] Trust in AI educational technology [ edit ] At present, teachers are still skeptical about AI due to two main factors: lack of knowledge and understanding of AI, as well as some misunderstandings about it. Because AI can only score based on written work, and teachers can sometimes understand what students want to express through text. So, teachers lack trust and have a negative attitude towards the use of AI-Edtech.[83] Challenges and criticism [ edit ] Challenges involved are mostly about over reliance on the technology could lead to lesser creativity, critical thinking and problem solving abilities especially if students skip traditional methods. Algorithm errors, hallucination are some of the common flaws found today in AI agents, which sometimes makes it unreliable and less trustworthy.[3] The increasing use of artificial intelligence tools by students for academic tasks has raised concerns about the potential adverse effects of widespread reliance on these tools on learning and the development of critical thinking skills. Reliance on generative artificial intelligence, for example, is linked with reduced academic self-esteem and performance, and heightened learned helplessness [84] - raising concerns about its unintended effects. The study also found that use of Generative AI for academic tasks was lower among students with the conscientiousness trait- suggesting that self-disciplined and goal-oriented individuals were less inclined to rely on AI tools in their academic work. These findings further underscore concerns raised in prior studies regarding academic integrity in the context of AI use in academic settings.[85] See also [ edit ]
2022-12-01T00:00:00
https://en.wikipedia.org/wiki/Artificial_intelligence_in_education
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39 Examples of Artificial Intelligence in Education
AI in Education: 39 Examples
https://onlinedegrees.sandiego.edu
[]
Curriculum Planning: AI helps educators plan curricula by analyzing educational data to identify trends and gaps. This ensures the curriculum remains relevant, ...
Artificial intelligence (AI) has rapidly transformed from a futuristic concept to an integral part of our daily lives, and education is no exception. In 2024, AI technologies are revolutionizing the academic landscape, offering unprecedented opportunities for personalized learning, administrative efficiency and improved educational outcomes. From intelligent tutoring systems to AI-driven classroom management, the impact of AI is profound and far-reaching. Educators and administrators can now leverage AI to analyze vast amounts of data, providing insights that drive informed decisions and strategies. Additionally, AI is breaking down education barriers thanks to tools that support students with different needs and learning styles. As AI evolves, its potential to transform education grows, setting the stage for a future where learning is more personalized and effective. So, exactly how can AI be used in education? Keep reading as we explore the applications and advancements that make AI in teaching beneficial for modern learners. 9 Benefits of AI in Education Artificial intelligence is no longer just a promise for the future — it’s actively enhancing education today. By integrating AI into classrooms, educators can personalize learning experiences, streamline administrative tasks and provide more effective support to students. Here are some of the specific benefits AI brings to the education sector: 1. Enhanced Personalized Learning AI tailors educational content to each student’s unique learning style and pace. For example, platforms like DreamBox and Smart Sparrow analyze student responses in real time to adapt lessons dynamically, enabling every student to master concepts at their own speed. 2. Automated Administrative Tasks AI automates grading, scheduling and report generation, significantly reducing the workload on educators. Tools like Gradescope provide consistent and objective grading of assignments, while AI scheduling software helps optimize class timetables and resource allocation. 3. More Engaged Learners AI makes learning more interactive and engaging through gamified content and adaptive learning platforms. Programs like Kahoot! and Minecraft: Education Edition use AI to create interactive quizzes and simulations that respond to student input, keeping learners motivated and involved. 4. Improved Accessibility AI-driven assistive technologies support students with disabilities, ensuring a more effective learning environment. Speech recognition software like Notta transcribes spoken words into text for hearing-impaired students, and AI-supported educational games provide personalized learning experiences for young children. 5. Actionable Insights AI analyzes vast amounts of educational data to provide educators with actionable insights. Platforms like Knewton Alta track student performance across various metrics, helping teachers identify learning gaps and adjust their instructional strategies accordingly. 6. More Efficient Classroom Management AI tools help teachers manage classroom behavior and engagement. For example, Classcraft uses AI to gamify classroom management, tracking student behavior and rewarding positive actions, which helps maintain a productive and motivated classroom environment. 7. Better Security and Assessment Integrity AI enhances the security and integrity of assessments through advanced proctoring and plagiarism detection. Tools like Turnitin check for originality in student submissions, and AI-supported proctoring systems monitor exam conditions to prevent cheating. 8. Continuous Lifelong Learning and Professional Development AI supports continuous learning and professional development for educators by recommending personalized resources and courses. Platforms like Edthena provide tailored learning paths based on educators’ career goals and teaching needs. 9. Greater Scalability AI enables the scaling of educational programs to accommodate more students without compromising quality. AI-based platforms can handle large volumes of data and provide personalized learning experiences to a growing number of learners, ensuring accessibility and consistency in education. 39 Examples of AI in Education Artificial intelligence is revolutionizing education with cutting-edge tools that enhance teaching and learning. From personalizing experiences to optimizing administrative tasks, here are 39 examples of how AI is transforming modern education: Adaptive Learning: AI-driven platforms assess students’ skill levels in real time and tailor instructional content to meet individual needs. These systems adapt lessons dynamically based on student responses, providing customized pathways to help students master concepts at their own pace. Assistive Technology: Tools such as speech recognition software transcribe spoken words into text, helping students with disabilities such as hearing impairments or dyslexia to participate more fully in the classroom by converting speech to text and vice versa. Data and Learning Analytics: AI helps analyze data from online learning portals, classroom attendance and grades. This data provides insights into student performance, helping educators identify trends and tailor instruction to address gaps in understanding and performance. Classroom Management: Platforms use AI to gamify classroom management. AI tracks student behavior and engagement, rewarding positive actions with points and badges and providing teachers with insights into classroom dynamics to manage and motivate students. Intelligent Tutoring Systems: AI-powered tutoring systems such as Carnegie Learning provide personalized feedback and support, adapting to individual learning styles and needs to help students understand complex concepts and improve academic performance. Automated Grading and Assessment Tools: These tools use AI to evaluate assignments and provide detailed feedback, streamlining the grading process, ensuring consistency and saving teachers time. AI can also grade more abstract assessments like essays by analyzing the content for coherence and relevance. Chatbots and Virtual Assistants: AI-driven chatbots such as Mainstay provide students with immediate support and assistance outside classroom hours. These chatbots answer questions, remind students of deadlines and guide them through administrative processes, enhancing engagement and promoting independent learning. Curriculum Planning: AI helps educators plan curricula by analyzing educational data to identify trends and gaps. This ensures the curriculum remains relevant, comprehensive and aligned with learning objectives by suggesting updates based on the latest educational needs and standards. Interactive and Learning Games: AI enhances educational games by creating engaging and adaptive learning experiences. These games use AI to provide tasks and challenges that adapt to student responses, promoting active participation and understanding of complex subjects. Personalized Learning: AI learning platforms create customized learning experiences by adapting to the unique ways students understand concepts. This reduces cognitive load and ensures that each student receives instruction tailored to their learning style and pace. Task Automation: AI automates routine tasks such as homework assessment, test grading and report generation. This enables educators to focus on more meaningful instructional activities and student interactions. Smart Content Creation: AI aids instructors in the creation of digital lessons and study materials. Tools like Magic School AI and Eduaide.AI simplify lesson planning, create assessments, write individualized education plans (IEPs), and much more to modernize learning and streamline instruction. Proctoring: AI-powered proctoring systems monitor exams to prevent cheating and ensure academic integrity. These systems analyze students’ behavior during exams, providing real-time alerts for suspicious activities and maintaining a secure testing environment. Language Learning: AI tools like Duolingo use adaptive algorithms to personalize language learning experiences. The AI adjusts the difficulty of exercises based on the user’s progress, ensuring an optimal learning curve and enhancing language acquisition. Closing the Skill Gap: AI identifies skill gaps in students by analyzing their performance data and provides targeted resources to address these deficiencies. This helps learners achieve proficiency in various subjects and prepares them for future academic challenges. Dyslexia Detection: AI tools such as Dysolve can detect dyslexia and other learning disabilities early on by analyzing reading patterns and errors. These tools provide tailored support and interventions to help affected students succeed, such as specialized reading programs and exercises. Edutainment and Gamification: AI integrates game elements into academic content, making learning fun and engaging. Platforms use AI to create interactive quizzes and games that promote deeper understanding and retention of educational material. Administrative Support: AI assists in administrative tasks such as scheduling, budgeting and resource allocation. Tools like Fetchy optimize educational operations by providing data-driven insights and recommendations, improving efficiency and reducing workload for educators. Virtual 3D Classrooms: The metaverse creates immersive virtual classrooms where students can interact with classmates and teachers. Platforms like Engage VR offer virtual environments that enhance the learning experience beyond traditional methods, providing opportunities for interactive and experiential learning. Digital Learning: AI enhances digital classrooms by providing immersive video content and interactive simulations. Tools like Nearpod use AI to deliver engaging and effective learning experiences through interactive lessons and real-time student feedback. Virtual Campus Activities: AI facilitates virtual extracurricular activities, allowing students to participate in clubs and events from anywhere in the world. Platforms like Remo use AI to create virtual spaces for networking and collaboration, enhancing student engagement beyond the classroom. Interdisciplinary Learning: AI breaks down barriers between subjects, promoting interdisciplinary learning. Tools like Wolfram Alpha use AI to demonstrate real-life applications of various theories, helping students understand the interconnectedness of different fields of study. Simulating Real-Life Situations: AI replicates real-life scenarios in virtual environments, allowing students to conduct experiments and learn through practical experience. Platforms like Labster offer virtual labs where students can safely explore and experiment with scientific concepts. Building Awareness: AI can teach students about social issues such as climate change and poverty. Tools like EarthSpeakr use AI to provide a deep emotional understanding alongside theoretical knowledge, promoting awareness and action on global challenges. Virtual Tours: AI-powered virtual tours enable students to explore different parts of the world from their classrooms. Platforms like Google Expeditions use AI to create immersive virtual field trips, broadening students’ horizons and enhancing their cultural understanding. These can also be useful in facilitating virtual tours of colleges. Guest Speakers and Events: AI facilitates virtual events and guest lectures, allowing students to learn from prominent figures and experts in various fields. Tools like BigMarker use AI to organize and manage virtual conferences, enhancing the learning experience through expert insights. Predictive Analytics: AI algorithms in learning analytics help educators spot trends and predict student performance, enabling early intervention for students who might struggle. Parent-Teacher Communication: AI-powered tools like Remind facilitate seamless communication between parents and teachers, allowing for real-time updates on student progress and classroom activities, thereby enhancing parental engagement and support in the education process. Test Prep: AI platforms like Magoosh provide personalized test preparation by analyzing student performance and adapting practice questions and study plans to focus on areas where students need the most improvement, thereby increasing their chances of success. Learning Management Systems (LMS): AI enhances LMS platforms by providing personalized learning paths, automating administrative tasks and offering data-driven insights into student performance and engagement. Professional Development: AI tools provide personalized professional development opportunities for educators by recommending courses and resources based on their career goals and teaching needs. Transportation: AI-powered systems optimize school bus routes, reducing travel time and improving safety. Tools like SafeStop use real-time data to track bus locations and provide parents with accurate arrival times, enhancing the overall efficiency of student transportation. Finance: AI assists educational institutions in managing their finances by analyzing spending patterns, predicting future expenses and identifying cost-saving opportunities. Tools like Allovue help schools allocate resources more effectively and improve financial planning. Cybersecurity: AI enhances the security of educational institutions by detecting and responding to cyber threats in real time. Tools like Darktrace use machine learning algorithms to identify unusual network activity, prevent data breaches and protect sensitive student information. Safety and Security: AI-powered surveillance systems monitor school premises for potential safety threats. Tools like Avigilon use AI to analyze video feeds and alert security personnel to suspicious activities, thereby enhancing the overall safety and security of the school environment. Plagiarism Detection: AI tools analyze student submissions for potential plagiarism by comparing them against a vast database of academic content, ensuring academic integrity and originality in student work. Enhanced Online Discussion Boards: AI enhances online discussion boards by moderating content, facilitating discussions and providing personalized feedback. Tools like Packback use AI to encourage critical thinking and engagement in online forums, creating a more dynamic and interactive learning environment. Academic Research: AI assists academic research by analyzing large datasets, identifying trends and generating insights. Tools like IBM Watson Discovery provide researchers with advanced analytics capabilities, helping them uncover new findings and accelerate the research process. Connected Campuses: AI integrates various campus systems to create a connected and efficient educational environment. Tools like Cisco Digital Network Architecture (DNA) use AI to manage and optimize campus infrastructure, enhancing connectivity and improving the overall campus experience. AI in Education: Universal Access Bernard Marr explains that AI tools can enhance universal access to education in a number of ways, including: Helping to “make global classrooms available to all, including those who speak different languages or who might have visual or hearing impairments” Creating access for “students who might not be able to attend school due to illness” Better serving “students who require learning at a different level or on a particular subject that isn’t available in their own school” Overall, it is hoped that AI will ultimately help educators make continued progress in addressing the broad range of physical, cognitive, academic, social and emotional factors that can affect student learning and ensure that all students have equal opportunity in education, regardless of their social class, race, gender, sexuality, ethnic background or physical and mental disabilities. AI in Education: Individualized Learning There is also considerable optimism around the idea that, as artificial intelligence becomes a more integral part of the classroom, teachers will be better equipped to offer an individualized learning experience for every student. According to an article in The Atlantic, (“Artificial Intelligence Promises a Personalized Education for All”), artificial intelligence holds the potential to “enhance human teachers’ abilities to tailor lessons to each student without knocking their class schedule off track,” eliminating the need for educators to “teach to the middle,” as often happens when their students have a range of skill levels and learning abilities. Rose Luckin, a professor of learning-centered design at University College London, is quoted as saying that, “The real power of artificial intelligence for education is in the way that we can use it to process vast amounts of data about learners, about teachers, about teaching and learning interactions.” Ultimately, AI can “help teachers understand their students more accurately, more effectively.” The Future of AI in Education Though there continues to be widespread debate over the pros and cons of deploying AI technology in the field of education, including the concerns about depersonalization and the ethical considerations cited above, there is an emerging consensus that the extraordinary range of current and future benefits will carry the day. This report on Artificial Intelligence in Education was developed by the University of San Diego’s innovative, online Master of Science in Applied Artificial Intelligence program, an AI industry thought leader and education partner.
2021-12-07T00:00:00
2021/12/07
https://onlinedegrees.sandiego.edu/artificial-intelligence-education/
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5 Pros and Cons of AI in the Education Sector | Walden University
5 Pros and Cons of AI in the Education Sector
https://www.waldenu.edu
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AI can empower educators, accelerate learning, and personalize educational experiences, quickly and easily.
Using artificial intelligence in education offers potential opportunities and advantages—but it also comes with challenges and potential drawbacks. In this exploration of the pros and cons of AI in education, we delve into potential benefits ranging from teaching assistance to individualized learning, while also shedding light on the ethical considerations surrounding bias, misinformation, and the future of educators’ roles. The intersection of AI and education is a dynamic landscape where innovation meets apprehension. It's critical to navigate this terrain thoughtfully. What is artificial intelligence? Artificial intelligence (AI) is a field of computer science and technology that focuses on creating machines, systems, or software programs capable of performing tasks that typically require human intelligence. These tasks include reasoning, problem solving, learning, perception, understanding natural language, and making decisions. AI systems are designed to simulate or replicate human cognitive functions and adapt to new information and situations. A brief history of artificial intelligence Artificial intelligence has been around for decades. In the 1950s, a computer scientist built Theseus, a remote-controlled mouse that could navigate a maze and remember the path it took.1 AI capabilities grew slowly at first. But advances in computer speed and cloud computing and the availability of large data sets led to rapid advances in the field of artificial intelligence. Now, anyone can access programs like ChatGPT, which is capable of having text-based conversations with users, and organizations are using AI for everything from developing driverless cars to reading radiographs to setting airline prices. The potential uses for AI are exciting—as well as concerning. Consider these pros and cons of using artificial intelligence in education. Five cons of AI in education Bias . Artificial intelligence is only as knowledgeable as the information it has been trained on. If a program like ChatGPT is trained on biased information, then when a student asks it a question, they could get a biased response, which can perpetuate stereotypes and social inequalities. If a biased AI tool is used for grading, students could receive low grades based on their race or gender. 2 . Artificial intelligence is only as knowledgeable as the information it has been trained on. If a program like ChatGPT is trained on biased information, then when a student asks it a question, they could get a biased response, which can perpetuate stereotypes and social inequalities. If a biased AI tool is used for grading, students could receive low grades based on their race or gender. Errors . In addition to bias, artificial intelligence may generate misinformation. The data that AI draws from may have errors, be outdated, or spread misinformation. Neither students nor teachers should assume that information provided by AI is accurate. 3 . In addition to bias, artificial intelligence may generate misinformation. The data that AI draws from may have errors, be outdated, or spread misinformation. Neither students nor teachers should assume that information provided by AI is accurate. Cheating . Students can use ChatGPT to write entire essays, answer quiz questions, or do their homework. Ironically, now there are AI programs that can detect AI writing to help teachers determine if their students are cheating. But sometimes those programs may falsely identify a student’s original work as plagiarism. . Students can use ChatGPT to write entire essays, answer quiz questions, or do their homework. Ironically, now there are AI programs that can detect AI writing to help teachers determine if their students are cheating. But sometimes those programs may falsely identify a student’s original work as plagiarism. Isolation . If students interact with a software program more than with a teacher, they can begin to feel disconnected and isolated. Their motivation and engagement may decrease, which could lead to an increase in dropout rates. 4 . If students interact with a software program more than with a teacher, they can begin to feel disconnected and isolated. Their motivation and engagement may decrease, which could lead to an increase in dropout rates. Jobs. Artificial intelligence has the potential to be a powerful learning tool. Some teachers worry that AI will replace them. Five pros of AI in education Assistance . Teachers who’ve tried AI have found that it can help make their jobs easier, from coming up with lesson plans to generating student project ideas to creating quizzes. With assistance from artificial intelligence, teachers can gain more time to spend with their students.3 . Teachers who’ve tried AI have found that it can help make their jobs easier, from coming up with lesson plans to generating student project ideas to creating quizzes. With assistance from artificial intelligence, teachers can gain more time to spend with their students.3 Speed . If a student feels “stuck” while working on an assignment, artificial intelligence programs can provide immediate, helpful assistance if a teacher or caregiver isn’t available. For instance, a student can ask, “How do I solve for X?” to be reminded of the steps for solving an equation. A student can even ask, “What are some effective strategies for improving my essay writing?” and ChatGPT can offer advice and resources right away. . If a student feels “stuck” while working on an assignment, artificial intelligence programs can provide immediate, helpful assistance if a teacher or caregiver isn’t available. For instance, a student can ask, “How do I solve for X?” to be reminded of the steps for solving an equation. A student can even ask, “What are some effective strategies for improving my essay writing?” and ChatGPT can offer advice and resources right away. Individualization . AI programs can help individualize learning opportunities for students. For instance, ChatGPT can quickly and easily translate materials to another language, making it easier for students who speak another language to understand assignments. ChatGPT can also revise materials so they are suitable for varying grade levels and tailor projects to suit students’ skills and interests. . AI programs can help individualize learning opportunities for students. For instance, ChatGPT can quickly and easily translate materials to another language, making it easier for students who speak another language to understand assignments. ChatGPT can also revise materials so they are suitable for varying grade levels and tailor projects to suit students’ skills and interests. Context . In a 2023 TED Talk, Sal Khan, the founder and CEO of Khan Academy, shared an example of an AI tutor that helped a student understand the symbolism of the green light in F. Scott Fitzgerald’s The Great Gatsby. The student asked the AI tutor to act as if it were the character Jay Gatsby and answer her question, “Why do you keep staring at the green light?” The AI tutor answered as Gatsby, giving her a response that was not only accurate, but elegant and contextual. 5 Future students could use AI to talk to Anne Frank about her life, to Marie Curie about her scientific discoveries, and to Shakespeare about his plays. . In a 2023 TED Talk, Sal Khan, the founder and CEO of Khan Academy, shared an example of an AI tutor that helped a student understand the symbolism of the green light in F. Scott Fitzgerald’s The Great Gatsby. The student asked the AI tutor to act as if it were the character Jay Gatsby and answer her question, “Why do you keep staring at the green light?” The AI tutor answered as Gatsby, giving her a response that was not only accurate, but elegant and contextual. Future students could use AI to talk to Anne Frank about her life, to Marie Curie about her scientific discoveries, and to Shakespeare about his plays. Personalization. Artificial intelligence can also personalize student learning. By analyzing student performance data, AI-powered tools can determine which students need support to improve their learning experience, and the best ways to help those students.6 Balancing the advantages of artificial intelligence in education with its potential drawbacks requires careful planning and consideration, as well as ongoing evaluation. AI can empower educators, accelerate learning, and personalize educational experiences, quickly and easily. On the other hand, the risks of bias, misinformation, and student isolation demand careful scrutiny. Teachers must explore the potential of AI in order to be effective advocates for their students and themselves. Be prepared to lead the classroom of the future by earning a degree in education from Walden University. With an MS in Education (MSEd) or a BS in Elementary Education (BSEE) degree, you can become an effective, engaging educator who uses technology to improve your students’ lives. Walden’s online teaching degree programs empower educators to gain new skills that they can put to use in the classroom to help their students thrive. Walden University is an accredited institution offering Master of Science in Education (MSEd) and Bachelor of Science in Elementary Education (BSEE) degree programs online. Expand your career options and earn your degree in a convenient, flexible format that fits your busy life. 1Source: ourworldindata.org/brief-history-of-ai 2Source: www.thaddeus.org/technical-blogs/the-impact-of-ai-bias-on-society 3Source: www.nea.org/nea-today/all-news-articles/chatgpt-enters-classroom-teachers-weigh-pros-and-cons 4Source: elearningindustry.com/pros-and-cons-of-using-ai-in-learning-chatgpt-helping-or-hindering-learning-outcomes 5Source: www.ted.com/talks/sal_khan_how_ai_could_save_not_destroy_education/transcript 6Source: www.forbes.com/sites/theyec/2023/02/21/ai-in-the-classroom-pros-cons-and-the-role-of-edtech-companies/?sh=241b9b36feb4 Walden University is accredited by the Higher Learning Commission, www.hlcommission.org.
2022-12-01T00:00:00
https://www.waldenu.edu/programs/education/resource/five-pros-and-cons-of-ai-in-the-education-sector
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Generative artificial intelligence (AI) in education - GOV.UK
Generative artificial intelligence (AI) in education
https://www.gov.uk
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AI has the power to transform education by helping teachers focus on what they do best: teaching. This marks a shift in how we use technology to enhance lives.
Introduction The Department for Education ( DfE ) is committed to supporting the AI Opportunities Action Plan. Generative artificial intelligence ( AI ) presents exciting opportunities to improve people’s lives, including by making our public services better. AI will support with the delivery of the Plan for Change and our opportunity mission. If used safely, effectively and with the right infrastructure in place, AI can support every child and young person, regardless of their background, to achieve at school and college and develop the knowledge and skills they need for life. Using AI in education settings: support materials provides free online support to help with the safe and effective use of AI in education. AI has the power to transform education by helping teachers focus on what they do best: teaching. This marks a shift in how we use technology to enhance lives and tap into the vast potential of AI in our classrooms. To make the opportunity a reality, we will continue to explore this technology safely to encourage innovation and maximise the benefits for education. Generative AI has demonstrated that it can help the education workforce by reducing some of the administrative burdens that hard-working teachers, staff and school leaders face in their day-to-day roles. Research demonstrates that generative AI could also be used for tasks such as feedback and tailored support in schools. Evidence is still emerging on the benefits and risks of pupils and students using generative AI themselves. We will continue to work with the education sector to develop understanding of effective and safe use cases. We will: consider the risks and challenges alongside the opportunities and benefits continue to work to ensure the safety and reliability of technology, including AI tools, to support teachers and learners tools, to support teachers and learners address the fundamental barriers to effective use, such as connectivity This statement is informed by: What is generative AI Generative AI is one type of AI . It refers to technology that can be used to create new content based on large volumes of data that models have been trained on a variety of sources. ChatGPT, Microsoft Copilot and Google Gemini are generative AI tools, built on large language models ( LLMs ). LLMs are a category of foundation models trained on large amounts of data, enabling them to understand and generate human-like content. Tools such as ChatGPT, Microsoft Copilot and Google Gemini can: answer questions complete written tasks generate images, text or code respond to prompts in a human-like way Other forms of generative AI can produce: audio simulations videos AI is the defining technology of our age, and it is evolving at incredible speed. This technology has the potential to benefit the economy and meet societal challenges. This is not new, and we already use AI in everyday life for: email spam filtering media recommendation systems navigation apps online chatbots Advances in technology mean that we can now use these tools to produce AI -generated content. This creates opportunities and challenges for the education sector. Opportunities and challenges for the education sector We have limited evidence on the impact of AI use in education on learners’ development, the relationship of AI use and educational outcomes, and the safety implications of children and young people using this technology in the classroom. We are working with the education sector, educational technology ( edtech ) industry, experts and academics to build evidence and support the education sector to use AI safely, responsibly and effectively. From our research and engagement with the sector, we have learned that generative AI could be used for: creating educational resources lesson and curriculum planning tailored feedback and revision activities administrative tasks supporting personalised learning When used appropriately, generative AI has the potential to: reduce workload across the education sector free up teachers’ time, allowing them to focus on delivering excellent teaching However, the content produced by generative AI could be: inaccurate inappropriate or unsafe biased taken out of context taken without permission (intellectual property infringement) out of date or unreliable low quality This is because generative AI : returns results based on its training dataset, which may not be specific to our curriculum stores and learns from input data – any data entered should not contain information that could allow an individual to be identified may not provide results that are comparable with a human-designed resource developed in the context of our curriculum can generate believable content, including credible scam emails can provide instructions for illegal or harmful activities can produce nonsensical, inaccurate or false information presented as fact, known as hallucination We see more immediate benefits and fewer risks from teacher-facing use of generative AI . If schools and colleges choose to use pupil-facing generative AI , they must take great care to ensure they are abiding by their legal responsibilities, including those related to: They should also consider possible impacts on learning, the importance of the teacher-learner relationship, and the risks of bias and misinformation. Teachers, leaders and staff must use their professional judgement when using these tools. Any content produced requires critical judgement to check for appropriateness and accuracy. The quality and content of any final documents remains the responsibility of the professional who produced it and the organisation they belong to, regardless of the tools or resources used. Generative AI tools can make certain written tasks quicker and easier, but it cannot replace the judgement and deep subject knowledge of a human expert. The education sector should: make the most of the opportunities that technology provides use technology safely and effectively to deliver excellent education that prepares pupils and students to contribute to society and the future workplace be aware of the limitations and risks of this technology Technology, including generative AI , should not replace the valuable relationship between teachers and pupils. Using AI safely and effectively Safety should be the top priority when deciding whether to use generative AI in your education setting Any use of generative AI by staff, students, and pupils should be carefully considered and assessed, evaluating the benefits and risks of use in its education setting. The intended use should be specified and have clear benefits that outweigh the risks. Different considerations will apply depending on whether it is staff or pupils (especially those under 18) using AI tools. Safety should not be compromised. Schools and colleges should also consider that there may be uses of generative AI by staff or pupils that have not been explicitly approved or adopted in their setting. Risk assessments should include plans for mitigating against unauthorised use cases. For example, students may use generative AI to create emails from the school to parents that seem realistic. Schools and colleges are free to make their own choices about the most suitable use cases for generative AI tools in their settings, as long as they comply with their wider statutory obligations such as keeping children safe in education. For example, schools and colleges may choose to only use AI tools with teachers, or only on administrative tasks. Others may choose to use AI tools with students, but only in particular subjects, year groups or key stages. Pupils should only be using generative AI in education settings with appropriate safeguards in place, such as close supervision and the use of tools with safety and filtering and monitoring features. For any use of AI , schools and colleges should: comply with age restrictions set by AI tools and open access LLMs tools and open access consider online safety, including AI , when creating and implementing their school or college approach to safeguarding and related policies and procedures , when creating and implementing their school or college approach to safeguarding and related policies and procedures consult Keeping children safe in education refer to our generative AI product safety expectations product safety expectations refer to the filtering and monitoring standards to make sure they have the appropriate systems in place, including filtering and monitoring approaches that cover generative AI . Keeping children safe in education provides schools and colleges with information on: what they need to do to protect pupils and students online their responsibilities with regards to limiting children’s exposure to risks from the school’s or college’s IT system how to review and strengthen their cyber security by referring to our guidance on cyber security standards for schools and colleges – generative AI could be used to increase the sophistication and credibility of attacks Schools and colleges may wish to review homework policies, and other types of unsupervised study to account for the availability of generative AI . This may include developing guidance on when it is acceptable or appropriate to use generative AI tools for educators, students and pupils. Schools and colleges may also wish to consider how they engage with parents around the use of AI tools. The following articles from the National Cyber Security Centre have more information on security and generative AI : Using AI responsibly Data privacy Personal data must be protected in accordance with data protection legislation. It is recommended that personal data is not used in generative AI tools. If it is strictly necessary to use personal data in generative AI tools within a setting, the school or college must ensure that all steps are taken to protect the data and the products and procedures comply with: data protection legislation their data privacy policies Schools and colleges should: be open and transparent where consideration is being given to the use of automated decision-making and profiling – this includes when they are developing their own in-house AI tools, such as AI chatbots or AI digital assistants tools, such as chatbots or digital assistants ensure the data subjects (pupils and parents or legal guardians) understand that their personal data is being processed using AI tools tools seek agreement to use data in an AI tool Use the guidance on Data protection in schools to find out more about: AI and data protection in schools and data protection in schools personal and special category data The Information Commissioner’s Office ( ICO ) has guidance on automated decision-making: What if we want to profile children or make automated decisions about them? Intellectual property Materials protected by copyright can only be used to train AI if there is permission from the copyright holder, or a statutory exception applies. Materials created by pupils and teachers may well be copyright material, assuming the statutory standard for what comprises copyright material is satisfied. This standard is generally considered to be low and does not factor in the quality of the work produced. Copyright law is distinct from data protection law, so any consents or data processing agreements for personal data are separate from issues of compliance with copyright law. Many free-to-access generative AI tools will use the inputs submitted by users to further train and refine their models. Some tools, largely paid tools, allow users to opt out of inputs being used to train the models. Examples of what may be deemed original creative work include: essays, homework or any other materials written or drawn by a student – it is unlikely that multiple-choice questions responses will constitute copyright work lesson plans created by a teacher prompts entered into generative AI tools Permission to use Schools and colleges must not allow or cause students’ original work to be used to train generative AI models unless they have permission, or an exception to copyright applies. Permission would need to be from the: student, as the copyright owner student’s parent or legal guardian, if the copyright owner is unable to consent because of being a minor Exceptions to copyright are limited, and settings may wish to take legal advice to ensure they are acting within the law. Secondary infringement Schools and colleges should also be aware of this risk of secondary infringement. This could happen if AI products are trained on unlicensed material and outputs and then used in educational settings or published more widely – for example, on a school or college website. Examples of this may include: publishing a policy that has been created by an AI tool that used input taken from another school or college’s policy without that setting’s permission tool that used input taken from another school or college’s policy without that setting’s permission using an image on a website that has been created by an AI tool using input taken from the copyright holder without their permission Higher-education settings may wish to review the intellectual asset management guide in regard to: developing student policies on the intellectual property they create how they interact and use intellectual property of others in light of generative AI Find out more about: The ICO has guidance on AI and data protection and what is personal data. Formal assessments Schools, colleges and awarding organisations need to continue taking reasonable steps where applicable, to prevent malpractice involving the use of generative AI . The Joint Council for Qualifications has published guidance on AI use in assessments. This guidance provides teachers and exam centres with information to help them prevent and identify potential malpractice involving the misuse of AI . It includes information on: what counts as AI misuse and real-life examples of malpractice misuse and real-life examples of malpractice the requirements for teachers and exam centres to help prevent and detect malpractice AI use and marking use and marking an expanded list of AI tools, including AI detection tools Ofsted’s and Ofqual’s approach Ofsted’s policy paper sets out its approach to artificial intelligence ( AI ). Ofsted supports the use of AI by providers where it improves the care and education of children and learners. It considers providers’ use of AI by the effect it has on the criteria set out in existing inspection frameworks and regulations. The paper also explains where AI could have the biggest benefits to Ofsted’s own work, including: in the risk assessment of good schools to automate tasks to generate new insights It will ensure these applications align with the regulatory principles of safety, transparency, fairness, accountability and contestability. Ofqual’s policy paper outlines its approach to regulating the use of artificial intelligence in the qualifications sector. Ofqual’s priority is to ensure that, where AI is used by awarding organisations, it is applied in a safe and appropriate way that does not threaten the fairness and standards of, or public confidence in, qualifications. This publication includes information on Ofqual’s regulatory position on: managing malpractice risks using AI to mark pupils’ and students’ work to mark pupils’ and students’ work using AI in remote invigilation The future for generative AI in education Investing in AI We are investing in resources to facilitate the safe, responsible and effective use of generative AI in the education sector. We have funded Oak National Academy to develop AI tools for teachers that will help to speed up lesson planning and reduce workloads. Oak recently launched Aila, an AI -powered lesson assistant. The ‘content store’ pilot is a £3 million pilot funded by the Department for Science, Innovation and Technology (DSIT), aiming to make available the underpinning content and data that are needed for great AI tools. DfE has awarded innovation funding through the AI tools for education competition to support innovators to develop tools based on this content. This aims to help reduce the burden of feedback and marking on teachers. Following the call for evidence, the main request from educators is further training and guidance on the safe use of AI . To respond to this, we are developing a training package with online resources and an online toolkit developed collaboratively with users. We are piloting an edtech evidence board. This will bring together a group of experts to assess and evaluate the evidence quality that edtech tools have a positive impact on teaching and learning against set criteria. This could then be shared with the sector to support and inform their technology choices. We are funding Ofsted to conduct a study to gather insights from early-adopter schools and further education colleges on the use of AI and the role leaders are playing. The aim of this research is to provide an up-to-date assessment of what emerging practice is developing, including: how providers are governing the use of AI monitoring the impact of AI on the provision of education and training, and providers’ understanding of risk to children, learners and staff We are continuing to seek opportunities to engage young people and parents directly on policy problems and policy co-design. We will continue to work with teachers, school leaders, support staff and experts to: consider and respond to the implications of generative AI and other emerging technologies and other emerging technologies support primary and secondary schools to teach a knowledge-rich computing curriculum to children up to 16 years old Further information Plan technology for your school is a digital service to help schools benchmark themselves against the digital standards and receive actionable next steps on how to meet them. Find out about AI : meeting the Public Sector Equality Duty (PSED) on the Equality and Human Rights Commission’s website. Support is available via the Intellectual Property Office’s online tools.
2022-12-01T00:00:00
https://www.gov.uk/government/publications/generative-artificial-intelligence-in-education/generative-artificial-intelligence-ai-in-education
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AI In Education: Home
AI In Education
https://www.ai-in-education.co.uk
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AI is transforming education. We want to ensure that the changes benefit pupils, teachers and society.
Our Mission We aim to ensure that AI will maximise the interests of all involved in education, students, teachers, support staff, parents, governors and the wider community. We want to do so by ensuring that AI enhances human intelligence and experience, and does so in a way that above all is to the benefit of the most vulnerable – including those with the least means, additional learning needs and those from diverse backgrounds. We are very clear of the risks of AI, which are very real.  Infantilisation of students (and staff)  Moral risk, not least through deep fake  Perceptions about cheating and dishonesty  Lack of responsibility – or answers to the question : who is in charge?  Impact on jobs The gains are many, but will only be realised if the risks are understood and addressed:  Personalised tuition  Personalised formative assessment  Opportunities for AI facilitated VR to enhance student experience of a range of STEM, social science and humanities subjects  Enhanced opportunities for students to learn at their own time, in their own way
2022-12-01T00:00:00
https://www.ai-in-education.co.uk/
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AI + Education = Simplified | Lance Eaton, Ph.D. | Substack
AI + Education = Simplified
https://aiedusimplified.substack.com
[ "Lance Eaton" ]
Blending AI, OER, and UDL. Actionable Insights for Generative AI, Accessibility, & Open Educational Resources.
This site requires JavaScript to run correctly. Please turn on JavaScript or unblock scripts
2022-12-01T00:00:00
https://aiedusimplified.substack.com/
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AI education - Raspberry Pi Foundation
AI education
https://www.raspberrypi.org
[ "Raspberry Pi Foundation" ]
Our free resources for AI education for teachers and young people in schools, clubs, and at home. Plus research and thought leadership.
Why kids still need to learn to code in the age of AI Rapid advances in generative AI are reshaping how we live and work. We argue that learning to code is essential to build the creative and critical thinking skills that young people need to thrive. Our position paper lays out five key reasons. open_in_new
2022-12-01T00:00:00
https://www.raspberrypi.org/teach/ai-education
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