Overcoming Legal Liability Obstacles to AI Adoption

One common obstacle to health care AI adoption is legal liability, which can be overcome with AI liability insurance. Ariel Dora Stern, PhD, Harvard-MIT Center for Regulatory Science faculty member and Associate Professor of Technology and Operations Management at Harvard Business School, describes how well-designed AI liability insurance can mitigate the predictable set of risks and uncertainties to adoption of AI in health care delivery, creating a positive feedback loop that encourages high-quality AI and leads to trust and greater AI implementation. This, in turn, will help mitigate the mismatch between the rapid pace of innovation and existing health care institutions and regulations.

The big challenge for health care delivery is overcoming institutional mismatch, according to Stern. “The technologies that have the greatest potential to transform health care delivery this includes, but is not limited, to AI would be unrecognizable to the 20th-century architects of our regulatory and health care delivery institutions,” says Stern. “And this problem is getting worse. The pace of innovation that we see today coupled with our rapidly transforming analytical and technological capabilities is increasingly mismatched to our existing institutions.” This mismatch underlies most of the challenges and opportunities in the adoption of AI in health care delivery. In driving innovation and adoption, incentives matter.