Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: ECCOLA -- a Method for Implementing Ethically Aligned AI Systems   Various recent Artificial Intelligence (AI) system failures, some of which
have made the global headlines, have highlighted issues in these systems. These
failures have resulted in calls for more ethical AI systems that better take
into account their effects on various stakeholders. However, implementing AI
ethics into practice is still an on-going challenge. High-level guidelines for
doing so exist, devised by governments and private organizations alike, but
lack practicality for developers. To address this issue, in this paper, we
present a method for implementing AI ethics. The method, ECCOLA, has been
iteratively developed using a cyclical action design research approach. The
method aims at making the high-level AI ethics principles more practical,
making it possible for developers to more easily implement them in practice.

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The categories of this paper are: adap-org
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The categories of this paper are: hep-ph
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The categories of this paper are: physics
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The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
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The categories of this paper are: plasm-ph
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The categories of this paper are: astro-ph
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The categories of this paper are: solv-int
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The categories of this paper are: hep-ex
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The categories of this paper are: eess
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The categories of this paper are: dg-ga
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The categories of this paper are: hep-th
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The categories of this paper are: q-fin
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The categories of this paper are: ao-sci
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The categories of this paper are: atom-ph
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The categories of this paper are: nucl-th