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Locating the work of artificial intelligence ethics

Author

Listed:
  • Stephen C. Slota
  • Kenneth R. Fleischmann
  • Sherri Greenberg
  • Nitin Verma
  • Brenna Cummings
  • Lan Li
  • Chris Shenefiel

Abstract

The scale and complexity of the data and algorithms used in artificial intelligence (AI)‐based systems present significant challenges for anticipating their ethical, legal, and policy implications. Given these challenges, who does the work of AI ethics, and how do they do it? This study reports findings from interviews with 26 stakeholders in AI research, law, and policy. The primary themes are that the work of AI ethics is structured by personal values and professional commitments, and that it involves situated meaning‐making through data and algorithms. Given the stakes involved, it is not enough to simply satisfy that AI will not behave unethically; rather, the work of AI ethics needs to be incentivized.

Suggested Citation

  • Stephen C. Slota & Kenneth R. Fleischmann & Sherri Greenberg & Nitin Verma & Brenna Cummings & Lan Li & Chris Shenefiel, 2023. "Locating the work of artificial intelligence ethics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(3), pages 311-322, March.
    • Handle: RePEc:bla:jinfst:v:74:y:2023:i:3:p:311-322
    DOI: 10.1002/asi.24638
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    References listed on IDEAS

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    1. Kenneth R. Fleischmann & Cindy Hui & William A. Wallace, 2017. "The Societal Responsibilities of Computational Modelers: Human Values and Professional Codes of Ethics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(3), pages 543-552, March.
    2. Samuele Lo Piano, 2020. "Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-7, December.
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    Cited by:

    1. Jiang, Yirui & Tran, Trung Hieu & Williams, Leon, 2023. "Machine learning and mixed reality for smart aviation: Applications and challenges," Journal of Air Transport Management, Elsevier, vol. 111(C).

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