Economics of Artificial Intelligence : Health Care Challenges

A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system.

In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI.

The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.

Ajay Agrawal is professor of strategic management and the Geoffrey Taber Chair in Entrepreneurship and Innovation at the University of Toronto as well as a research associate of the NBER. 

Joshua Gans is professor of strategic management and holder of the Jeffrey S. Skoll Chair of Technical Innovation and Entrepreneurship at the Rotman School of Management, University of Toronto (with a cross appointment in the Department of Economics), and a research associate of the NBER.

Avi Goldfarb holds the Rotman Chair in Artificial Intelligence and Healthcare and is professor of marketing at the Rotman School of Management, University of Toronto, and a research associate of the NBER.

Catherine E. Tucker is the Sloan Distinguished Professor of Management Science at MIT Sloan and a research associate of the NBER.