A Products Liability Framework for AI

Abstract

A products liability framework, drawing inspiration from the regulation of FDA-approved medical products—which includes federal regulation as well as products liability—holds great promise for tackling many of the challenges AI poses. Notwithstanding the new challenges that sophisticated AI technologies pose, products liability provides a conceptual framework capable of responding to the learning and iterative aspects of these technologies. Moreover, this framework provides a robust model of the feedback loop between tort liability and regulation.
The regulation of medical products provides an instructive point of departure. The FDA has recognized the need to revise its traditional paradigm for medical device regulation to fit adaptive AI/ML technologies, which enable continuous improvements and modifications to devices based on information gathered during use. AI/ML technologies should hasten an even more significant regulatory paradigm shift at the FDA away from a model that puts most of its emphasis on (and resources into) ex ante premarket approval to one that highlights ongoing postmarket surveillance. As such a model takes form, products liability should continue to play a significant information-production and deterrence role, especially during the transition period before a new ex post regulatory framework is established.