Moral Engagement and Disengagement in Health Care AI Development.

Journal: AJOB empirical bioethics
PMID: 38588388

Abstract

BACKGROUND: Machine learning (ML) is utilized increasingly in health care, and can pose harms to patients, clinicians, health systems, and the public. In response, regulators have proposed an approach that would shift more responsibility to ML developers for mitigating potential harms. To be effective, this approach requires ML developers to recognize, accept, and act on responsibility for mitigating harms. However, little is known regarding the perspectives of developers themselves regarding their obligations to mitigate harms.

Authors

  • Ariadne A Nichol
    Stanford School of Medicine, Stanford Center for Biomedical Ethics, Stanford, CA, United States.
  • Meghan Halley
    Center for Biomedical Ethics, Stanford University School of Medicine, Stanford, California, USA.
  • Carole Federico
    Center for Biomedical Ethics, Stanford University School of Medicine, Stanford, California, USA.
  • Mildred K Cho
    Stanford School of Medicine, Stanford Center for Biomedical Ethics, Stanford, CA, United States.
  • Pamela L Sankar
    Department of Medical Ethics and Health Policy, Perelman School of Medicine, Philadelphia, PA, United States.

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