Nature paper reframes AI healthcare liability across 31 US cases

Physicians are being made to answer for AI harms that originate elsewhere in the healthcare system. That is the argument advanced by Gennie Mansi and Mark Riedl of the Georgia Institute of Technology in a new Nature Health analysis of 31 US legal cases and reported harms.

"Patients' medical care relies on a complex web of stakeholders—physicians, state health departments, health insurers and care facilities, among others—and many AI tools deployed across their healthcare delivery negatively impact their care," the authors write in Nature Health. Because AI tools reach patients through coverage decisions, eligibility screening, and triage as much as through the exam room, "patients have had no option but to seek legal recourse for harms."

The case pool draws on three open databases: DAIL, the AI, Algorithmic and Automation Incidents (AIAAIC) database, and the Health Litigation Tracker. Systems named in the paper include the nH Predict system, the Oregon DHS Safety at Screening Tool, and the Babylon Health Triage System.

The paper proposes two reforms. First, change liability structures so they reflect the many parties shaping how AI reaches patients. Second, design tools that help patients' lawyers "provide critical legal expertise and practically support recourse for patients" — a design brief aimed at advocates rather than at clinicians.

The abstract names no cases and reports no damages, verdicts, or the specific theories of liability on which claims turned.