Academic machine learning researchers' ethical perspectives on algorithm development for health care: a qualitative study.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Feb 16, 2024

Abstract

OBJECTIVES: We set out to describe academic machine learning (ML) researchers' ethical considerations regarding the development of ML tools intended for use in clinical care.

Authors

  • Max Kasun
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, United States.
  • Katie Ryan
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, United States.
  • Jodi Paik
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, United States.
  • Kyle Lane-McKinley
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, United States.
  • Laura Bodin Dunn
    Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, AK 72205, United States.
  • Laura Weiss Roberts
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, United States.
  • Jane Paik Kim
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, United States.

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