• T J Kasperbauer.
• Indiana University Center for Bioethics, Indiana University School of Medicine, Indianapolis, Indiana, USA.
• J Eval Clin Pract. 2021 Jun 1; 27 (3): 537-542.

AbstractThe goals of learning health systems (LHS) and of AI in medicine overlap in many respects. Both require significant improvements in data sharing and IT infrastructure, aim to provide more personalized care for patients, and strive to break down traditional barriers between research and care. However, the defining features of LHS and AI diverge when it comes to the people involved in medicine, both patients and providers. LHS aim to enhance physician-patient relationships while developments in AI emphasize a physicianless experience. LHS also encourage better coordination of specialists across the health system, but AI aims to replace many specialists with technology and algorithms. This paper argues that these points of conflict may require a reconsideration of the role of humans in medical decision making. Although it is currently unclear to what extent machines will replace humans in healthcare, the parallel development of LHS and AI raises important questions about the exact role for humans within AI-enabled healthcare.© 2020 John Wiley & Sons, Ltd.

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