Artificial Intelligence and Liability in Medicine: Balancing Safety and Innovation

George Maliha, Sara Gerke, I. Glenn Cohen, Ravi B. Parikh

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

Policy Points With increasing integration of artificial intelligence and machine learning in medicine, there are concerns that algorithm inaccuracy could lead to patient injury and medical liability. While prior work has focused on medical malpractice, the artificial intelligence ecosystem consists of multiple stakeholders beyond clinicians. Current liability frameworks are inadequate to encourage both safe clinical implementation and disruptive innovation of artificial intelligence. Several policy options could ensure a more balanced liability system, including altering the standard of care, insurance, indemnification, special/no-fault adjudication systems, and regulation. Such liability frameworks could facilitate safe and expedient implementation of artificial intelligence and machine learning in clinical care.

Original languageEnglish (US)
Pages (from-to)629-647
Number of pages19
JournalMilbank Quarterly
Volume99
Issue number3
DOIs
StatePublished - Sep 2021

All Science Journal Classification (ASJC) codes

  • Health Policy
  • Public Health, Environmental and Occupational Health

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