Mello, M. M., & Guha, N. (2024).
The New England journal of medicine, 390(3), 271–278. https://doi.org/10.1056/NEJMhle2308901
Optimism about the explosive potential of artificial intelligence (AI) to transform medicine is tempered by worry about what it may mean for the clinicians being "augmented." One question is especially problematic because it may chill adoption: when Al contributes to patient injury, who will be held responsible?
Some attorneys counsel health care organizations with dire warnings about liability1 and dauntingly long lists of legal concerns. Unfortunately, liability concern can lead to overly conservative decisions, including reluctance to try new things. Yet, older forms of clinical decision support provided important opportunities to prevent errors and malpractice claims. Given the slow progress in reducing diagnostic errors, not adopting new tools also has consequences and at some point may itself become malpractice. Liability uncertainty also affects Al developers' cost of capital and incentives to develop particular products, thereby influencing which Al innovations become available and at what price.
To help health care organizations and physicians weigh Al-related liability risk against the benefits of adoption, we examine the issues that courts have grappled with in cases involving software error and what makes them so challenging. Because the signals emerging from case law remain somewhat faint, we conducted further analysis of the aspects of Al tools that elevate or mitigate legal risk. Drawing on both analyses, we provide risk-management recommendations, focusing on the uses of Al in direct patient care with a "human in the loop" since the use of fully autonomous systems raises additional issues.
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The Awkward Adolescence of Software-Related Liability
Legal precedent regarding Al injuries is rare because Al models are new and few personal-injury claims result in written opinions. As this area of law matures, it will confront several challenges.
Challenges in Applying Tort Law Principles to Health Care Artificial Intelligence (AI).
Ordinarily, when a physician uses or recommends a product and an injury to the patient results, well-established rules help courts allocate liability among the physician, product maker, and patient. The liabilities of the physician and product maker are derived from different standards of care, but for both kinds of defendants, plaintiffs must show that the defendant owed them a duty, the defendant breached the applicable standard of care, and the breach caused their injury; plaintiffs must also rebut any suggestion that the injury was so unusual as to be outside the scope of liability.
The article is paywalled, which is not how this should work.
