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Distinguishing two features of accountability for AI technologies

Nature Machine Intelligence volume 4, pages 734–736 (2022)Cite this article

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Policymakers and researchers consistently call for greater human accountability for AI technologies. We should be clear about two distinct features of accountability.

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Acknowledgements

We thank P. Noordhof and T. Stoneham for their comments. This work was supported by the Engineering and Physical Sciences Research Council (EP/W011239/1) and the Assuring Autonomy International Programme, a partnership between Lloyd’s Register Foundation and the University of York.

Author information

Authors and Affiliations

  1. Assuring Autonomy International Programme, Institute for Safe Autonomy, University of York, York, UK

    Zoe Porter, John McDermid, Tom Lawton & Ibrahim Habli

  2. Department of Computer Science, University of York, York, UK

    Zoe Porter, John McDermid & Ibrahim Habli

  3. Department of Philosophy, University of Wisconsin-Madison, Madison, WI, USA

    Annette Zimmermann

  4. Carr Center for Human Rights Policy, Harvard University, Cambridge, MA, USA

    Annette Zimmermann

  5. York Law School, University of York, York, UK

    Phillip Morgan

  6. Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK

    Tom Lawton

Authors
  1. Zoe Porter
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  2. Annette Zimmermann
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  3. Phillip Morgan
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  4. John McDermid
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  6. Ibrahim Habli
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Corresponding author

Correspondence to Zoe Porter.

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Competing interests

T.L. is Head of Clinical AI at Bradford Teaching Hospitals NHS Foundation Trust. The remaining authors declare no competing interests.

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Nature Machine Intelligence thanks Jacob Metcalf and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Porter, Z., Zimmermann, A., Morgan, P. et al. Distinguishing two features of accountability for AI technologies. Nat Mach Intell 4, 734–736 (2022). https://doi.org/10.1038/s42256-022-00533-0

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