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Updated: Dec 7, 2025

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

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When Does Physician Use of AI Increase Liability?

Kevin Tobia1,2, Aileen Nielsen2, Alexander Stremitzer2

  • 1Georgetown University Law Center, Washington, DC; and kevin.tobia@georgetown.edu.

Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine
|September 26, 2020
PubMed
Summary

Physicians using artificial intelligence (AI) medical advice may face malpractice liability. Juror judgments show accepting AI standard care recommendations reduces liability risk, but rejecting nonstandard AI advice does not shield physicians from malpractice claims.

Keywords:
artificial intelligenceliabilityprecision medicine

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Last Updated: Dec 7, 2025

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

616

Area of Science:

  • Medical Law
  • Artificial Intelligence in Medicine
  • Medical Malpractice

Background:

  • Automated and artificial intelligence (AI) systems increasingly provide medical treatment recommendations, sometimes deviating from standard care.
  • Legal scholars express concern that following nonstandard AI recommendations could increase physician liability in medical malpractice cases.
  • Physician liability when using AI systems is influenced by lay juror judgments.

Purpose of the Study:

  • To investigate potential jurors' judgments of physician liability when AI systems provide medical treatment recommendations.
  • To determine how AI recommendations (standard vs. nonstandard care) and physician decisions (accept vs. reject) influence perceived liability.

Main Methods:

  • An online experimental study was conducted with a nationally representative sample of 2,000 U.S. adults.
  • Participants were presented with one of four scenarios involving an AI treatment recommendation and a physician's subsequent decision, which resulted in harm.
  • Participants assessed the physician's liability based on the presented scenario.

Main Results:

  • Physicians accepting AI recommendations for standard care showed a reduced risk of liability compared to rejecting them.
  • When AI recommended nonstandard care, rejecting the advice and providing standard care did not offer a similar liability-shielding effect.
  • Juror perceptions of liability are influenced by the interplay between AI recommendations and physician actions.

Conclusions:

  • The tort law system is unlikely to hinder the adoption of AI in precision medicine.
  • Current legal frameworks may even encourage the use of AI precision medicine tools by physicians.
  • Understanding juror perceptions is crucial for navigating the legal landscape of AI in healthcare.