Advances in healthcare artificial intelligence (AI) will seriously challenge the robustness and appropriateness of our current healthcare regulatory models. These models primarily regulate medical persons using the “practice of medicine” touchstone or medical machines that meet the FDA definition of “device.” However, neither model seems particularly appropriate for regulating machines practicing medicine or the complex man-machine relationships that will develop.
Artificial intelligence (AI) looks to transform the practice of medicine. As academics and policymakers alike turn to legal questions, a threshold issue involves what role AI will play in the larger medical system.
We are witnessing an interesting juxtaposition in medical decision-making. Increasingly, health providers are moving away from traditional substitute decision-making for patients who have lost decisional capacity, towards supported decision-making. Supported decision-making increases patient autonomy as the patient—with the support and assistance of others—remains the final decisionmaker. By contrast, doctors’ decision-making capacity is diminishing due to the increasing use of AI to diagnose and treat patients.
The ‘Revised Common Rule’ took effect on January 21, 2019, marking the first change since 2005 to the federal regulation that governs human subjects research conducted with federal support or in federally supported institutions. The Common Rule had required informed consent before researchers could collect and use identifiable personal health information.
For well over a decade the U.S. Food and Drug Administration (FDA) has been told that its framework for regulating traditional medical devices is not modern or flexible enough to address increasingly novel digital health technologies. Very recently, however, the FDA introduced a series of digital health initiatives that represent important experiments in medical product regulation, departing from longstanding precedents applied to therapeutic products like drugs and devices.