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.

Since 1992 the Department of Defense (DOD), through the U.S. Army Medical Research and Material Command, has received congressionally earmarked appropriations for programs of biomedical research on prostate, breast, and ovarian cancer; neurofibromatosis; tuberous sclerosis; and other health problems. Appropriations for these Congressionally Directed Medical Research Programs are used to support peer reviewed extramural research project, training, and infrastructure grants. Congress has become concerned about funding increases for these programs given current demands on the military budget. At the request of Congress, the Institute of Medicine (IOM) examined possibilities of augmenting program funding from alternative sources. The resulting IOM book, Strategies to Leverage Research Funding: Guiding DOD's Peer Reviewed Medical Research Programs, focuses on nonfederal and private sector contributions that could extend the appropriated funds without biasing the peer review project selection process.

A calculation of the social returns to innovation /Benjamin F. Jones and Lawrence H. Summers --Innovation and human capital policy /John Van Reenen --Immigration policy levers for US innovation and start-ups /Sari Pekkala Kerr and William R. Kerr --Scientific grant funding /Pierre Azoulay and Danielle Li --Tax policy for innovation /Bronwyn H. Hall --Taxation and innovation: what do we know? /Ufuk Akcigit and Stefanie Stantcheva --Government incentives for entrepreneurship /Josh Lerner.

Gain a head start in your academic career with this step-by-step guide to building an externally funded research program.

Threatened by sharp cuts in state government support and stagnant federal research funding, US public research universities are becoming fragile ecosystems. By charting flows of research dollars through a leading public research university-the University of California, San Francisco (UCSF)-this book illuminates how such schools work to cope with these funding threats and how the challenges and coping strategies affect organization and direction of research. Academic leaders, faculty, administrators, and students will learn how a complex academic health center manages its revenues, expenses, and diverse academic cultures. For the first time, they can begin to understand arcane mysteries of indirect cost recovery, sponsored funds, capital investment, endowments, debt, and researchers' salaries.