Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Clinical decisions using AI must consider patient values

Nature Medicine volume 28, pages 229–232 (2022)Cite this article

Subjects

Built-in decision thresholds for AI diagnostics are ethically problematic, as patients may differ in their attitudes about the risk of false-positive and false-negative results, which will require that clinicians assess patient values.

Recent years have seen a surge of interest in medical applications of machine learning and artificial intelligence (AI) — and in the ethics of these applications1,2. In the near future, it is unlikely that AI technology will replace human decision-makers, but it is likely to assist human decision-makers in many contexts3. For example, machine learning can assist with the diagnosis of cancer from imaging data4, the mapping of the boundaries of tumors5, the treatment of sepsis6, the classification of field-based rapid HIV tests7 and the diagnosis of cognitive-motor dissociation in unresponsive patients with brain injuries8.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Get just this article for as long as you need it

$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Six possible decision pathways using AI algorithms for breast cancer screening.

References

  1. McCradden, M. D. et al. Nat. Med. 26, 1325–1326 (2020).

    Article  CAS  Google Scholar 

  2. Grote, T. & Berens, P. J. Med. Ethics 46, 205–211 (2019).

    Article  Google Scholar 

  3. Tschandl, P. et al. Nat. Med. 26, 1229–1234 (2020).

    Article  CAS  Google Scholar 

  4. McKinney, S. M. et al. Nature 577, 89–94 (2020).

    Article  CAS  Google Scholar 

  5. Liu, Z. et al. Phys. Med. Biol. 66, 124002 (2021).

    Article  Google Scholar 

  6. Komorowski, M. et al. Nat. Med. 24, 1716–1720 (2018).

    Article  CAS  Google Scholar 

  7. Turbé, V. et al. Nat. Med. 27, 1165–1170 (2021).

    Article  Google Scholar 

  8. Claassen, J. et al. N. Engl. J. Med. 380, 2497–2505 (2019).

    Article  Google Scholar 

  9. Hastie, T. The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Springer, 2009).

  10. Plutynski, A. in Exploring Inductive Risk: Case Studies of Values in Science (eds. Elliott, K. C. & Richards, T.) 149–170 (Oxford University Press, 2017).

  11. Douglas, H.E. Science, Policy, and the Value-free Ideal (University of Pittsburgh Press, 2009).

  12. Bright, L. K. Synthese 195, 2227–2245 (2017).

    Article  Google Scholar 

  13. Wenner, D. M. Int. J. Fem. Approaches Bioeth. 13, 28–48 (2020).

    Article  Google Scholar 

  14. Buchak, L. J. Med. Ethics 43, 90–95 (2016).

    Article  Google Scholar 

  15. Pan, C. H. & Statman, M. J. Invest. Consult. 13, 54–63 (2012).

    Google Scholar 

  16. Ongena, Y. P. et al. J. Am. Coll. Radiol. 18, 79–86 (2021).

    Article  Google Scholar 

  17. Birch, J., Creel, K., Jha, A. & Plutynski, A. Zenodo https://doi.org/10.5281/zenodo.5589207 (2021).

  18. Nagler, R. H. et al. Med. Care 55, 879–885 (2017).

    Article  Google Scholar 

Download references

Acknowledgements

We thank S. Bhalla, L. Kofi Bright, A. Houston, L. Hudetz, R. Short, J. Swamidass, K. Vredenburgh, Z. Ward, K. Wright and patient groups at Washington University in St Louis, Stanford University and Johns Hopkins University for their input and advice. A.K.J. acknowledges support from the National Institute of Biomedical Imaging and Bioengineering of the US National Institutes of Health (R01-EB031051 and R56-EB028287).

Author information

Authors and Affiliations

  1. Centre for Philosophy of Natural and Social Science, London School of Economics and Political Science, London, UK

    Jonathan Birch

  2. McCoy Family Center for Ethics in Society and the Institute for Human-Centered Artificial Intelligence, Stanford University, Stanford, CA, USA

    Kathleen A. Creel

  3. Department of Biomedical Engineering and Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA

    Abhinav K. Jha

  4. Department of Philosophy and Division of Biology and Biomedical Sciences, Washington University in St Louis, St Louis, MO, USA

    Anya Plutynski

Authors
  1. Jonathan Birch
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kathleen A. Creel
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Abhinav K. Jha
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Anya Plutynski
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to conceptualization, methodology (survey design), investigation (consulting patients), and writing (review and editing). J.B. wrote the original draft.

Corresponding author

Correspondence to Jonathan Birch.

Ethics declarations

Competing interests

The authors declare no competing interests.

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Birch, J., Creel, K.A., Jha, A.K. et al. Clinical decisions using AI must consider patient values. Nat Med 28, 229–232 (2022). https://doi.org/10.1038/s41591-021-01624-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41591-021-01624-y

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer