Applying a Common Enterprise Theory of Liability to Clinical AI Systems. Issue 4 (December 2021)

• Record Type: Journal Article
• Authors: Chan, Benny
• Is Part Of: American journal of law & medicine. Volume 47:Issue 4(2021)
• Page Start: 351
• Page End: 385
• Publication Date: 2021-12
• Subjects: Medical jurisprudence -- United States -- Periodicals; Medical laws and legislation -- United States -- Periodicals; Jurisprudence -- Periodicals; Medicine -- Periodicals; Legislation as Topic -- Periodicals; Jurisprudence; Medicine; Legislation as Topic; Medical jurisprudence; Medical laws and legislation; United States; Electronic journals; 344.7304105
• DOI: 10.1017/amj.2022.1
• Languages: English
• ISSNs: 0098-8588

Abstract

Abstract : The advent of artificial intelligence ("AI") holds great potential to improve clinical diagnostics. At the same time, there are important questions of liability for harms arising from the use of this technology. Due to their complexity, opacity, and lack of foreseeability, AI systems are not easily accommodated by traditional liability frameworks. This difficulty is compounded in the health care space where various actors, namely physicians and health care organizations, are subject to distinct but interrelated legal duties regarding the use of health technology. Without a principled way to apportion responsibility among these actors, patients may find it difficult to recover for injuries. In this Article, I propose that physicians, manufacturers of clinical AI systems, and hospitals be considered a common enterprise for the purposes of liability. This proposed framework helps facilitate the apportioning of responsibility among disparate actors under a single legal theory. Such an approach responds to concerns about the responsibility gap engendered by clinical AI technology as it shifts away from individualistic notions of responsibility, embodied by negligence and products liability, toward a more distributed conception. In addition to favoring plaintiff recovery, a common enterprise strict liability approach would create strong incentives for the relevant actors to take care.