AMA advances framework for clinical AI liability

CHICAGO - As AI takes on an expanding role in clinical care, questions about who is responsible when these technologies cause patient harm become increasingly urgent. The American Medical Association (AMA) Center for Digital Health and AI is advancing a new framework for aligning liability with each party's authority and ability to prevent or mitigate harm.

Existing liability frameworks were not designed for technologies in which physicians, developers, and healthcare organizations each exercise different levels of control over clinical AI systems. As a result, physicians may face liability for risks they cannot reasonably prevent, while patients may struggle to seek remedies when AI causes harm.

"Patients must have meaningful avenues for recourse when clinical AI causes harm, and physicians must be able to use these technologies with confidence that responsibility reflects what they can reasonably know and control," said the AMA President Willie Underwood III, MD, MSc, MPH. "As AI assumes more clinical functions, developers, healthcare organizations and physicians each have important responsibilities. We need clear expectations that protect patients, support sound clinical judgment, and ensure accountability remains with those best positioned to prevent harm."

The AMA is calling for an approach that establishes well-defined, complementary responsibilities across the clinical AI lifecycle:

• Developers and manufacturers should demonstrate and maintain the safety and effectiveness of their products and address risks within their control.
• Healthcare organizations and other deployers should be accountable for how AI systems are selected, implemented, governed and monitored in real-world settings.
• Physicians should be responsible for the clinical judgment they can meaningfully exercise, based on the system's intended use, known limitations and the information available at the point of care.
• Patients must retain meaningful avenues for seeking accountability and appropriate remedies when harm results from defective AI systems or other actionable failures.

The framework recognizes that multiple parties may bear liability for the use of AI when something goes wrong, with accountability aligned with each party's ability to prevent harm. It also emphasizes that physician oversight cannot substitute for adequate evidence, appropriate system design or the conditions necessary to make clinical review meaningful.