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Ethics methods are required as part of reporting guidelines for artificial intelligence in healthcare

Nature Machine Intelligence volume 4, pages 316–317 (2022)Cite this article

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To the Editor — The evaluation of health technologies, such as artificial intelligence (AI), through robust, reliable and reproducible scientific research is one of the cornerstones of evidence-based medicine and ethical patient care. Although completeness of reporting is imperative for all scientific endeavours, it is of particular importance within the health sciences as scientific and ethical transgressions may manifest in harm to individual patients or impose disparate quality of care across patient populations1.

Reporting guidelines reflect ethical commitments to transparency and honesty in science. However, reporting guidelines in the health sciences have so far not included much detail related to the ethical dimensions of study design or conduct. Typically, the only requirements are that Ethical Review Board (ERB) approval is noted along with a statement confirming that participants provided informed consent when consent is required. Details regarding the specific ethical challenges involved and the methods used to address them are not typically described. This state of affairs suggests that the ethical aspects of study design are not salient vis-à-vis the critical appraisal or replication of the studies in question.

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Acknowledgements

Infrastructure support for this research was provided by the National Institute for Health Research Imperial Biomedical Research Centre (BRC), UK.

Author information

Author notes

  1. These authors contributed equally: Viknesh Sounderajah, Melissa D. McCradden, Xiaoxuan Liu, Sherri Rose.

  2. These authors jointly supervised this work: Patrick M. Bossuyt, David Moher, Ara Darzi.

Authors and Affiliations

  1. Institute of Global Health Innovation, Imperial College London, London, UK

    Viknesh Sounderajah, Hutan Ashrafian & Ara Darzi

  2. Department of Bioethics, The Hospital for Sick Children, Toronto, ON, Canada

    Melissa D. McCradden & James Anderson

  3. Genetics & Genome Biology, Peter Gilgan Centre for Research & Learning, Toronto, ON, Canada

    Melissa D. McCradden

  4. Division of Clinical and Public Health, Dalla Lana School of Public Health, Toronto, ON, Canada

    Melissa D. McCradden

  5. Institute of Inflammation and Ageing, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK

    Xiaoxuan Liu

  6. Center for Health Policy and Department of Health Policy, Stanford University, CA, USA

    Sherri Rose

  7. NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK

    Gary S. Collins

  8. Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK

    Gary S. Collins

  9. Institute for Health Management Policy & Evaluation, University of Toronto, Toronto, ON, Canada

    James Anderson

  10. Department of Epidemiology and Data Science, Amsterdam University Medical Centre, University of Amsterdam, Amsterdam, the Netherlands

    Patrick M. Bossuyt

  11. Ottawa Hospital Research Institute, Ottawa, ON, Canada

    David Moher

Authors
  1. Viknesh Sounderajah
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  10. Ara Darzi
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Contributions

All authors contributed equally to the conception, writing and revision of this manuscript.

Corresponding author

Correspondence to Viknesh Sounderajah.

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Competing interests

The authors declare no competing interests.

Additional information

Declaration: The lead author affirms that this manuscript is an honest, accurate and transparent account of the study being reported.

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Sounderajah, V., McCradden, M.D., Liu, X. et al. Ethics methods are required as part of reporting guidelines for artificial intelligence in healthcare. Nat Mach Intell 4, 316–317 (2022). https://doi.org/10.1038/s42256-022-00479-3

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