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Patient wisdom should be incorporated into health AI to avoid algorithmic paternalism

Nature Medicine volume 29, pages 765–766 (2023)Cite this article

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The first interactive computer, ELIZA, was created by Joseph Weizenbaum in 1972, who remarked: “Most of the damage that the computer could potentially cause depends less on what the computer actually can or cannot do than on the qualities that the public attributes to the computer.” As artificial intelligence (AI) advances into medicine, narratives of “AI versus clinicians,” and “AI outperforms doctors” dominate public discourse, sometimes positioning AI as a superior form of knowledge. As a result, some clinicians worry about the relevance of clinical judgment, patients get conflicting messages about whom to trust, and the general uncertainty about where AI fits within the evidence-based medicine paradigm continues to hinder translation into the clinic1.

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Authors and Affiliations

  1. Bioethics Department, The Hospital for Sick Children, Toronto, Ontario, Canada

    Melissa D. McCradden & Roxanne E. Kirsch

  2. Genetics & Genome Biology, Peter Gilgan Centre for Research and Learning, The Hospital for Sick Children, Toronto, Ontario, Canada

    Melissa D. McCradden

  3. Division of Clinical and Public Health, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada

    Melissa D. McCradden

  4. Critical Care Medicine Department, The Hospital for Sick Children, Toronto, Ontario, Canada

    Roxanne E. Kirsch

  5. Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada

    Roxanne E. Kirsch

Authors
  1. Melissa D. McCradden
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  2. Roxanne E. Kirsch
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Corresponding author

Correspondence to Melissa D. McCradden.

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Competing interests

M.D.M. and R.K. have no conflicts of interest related to this manuscript.

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McCradden, M.D., Kirsch, R.E. Patient wisdom should be incorporated into health AI to avoid algorithmic paternalism. Nat Med 29, 765–766 (2023). https://doi.org/10.1038/s41591-023-02224-8

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  • DOI: https://doi.org/10.1038/s41591-023-02224-8

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