The Economics of Artificial Intelligence

Advances in artificial intelligence (AI) highlight the potential of this technology to affect productivity, growth, inequality, market power, innovation, and employment. This volume seeks to set the agenda for economic research on the impact of AI. It covers four broad themes: AI as a general purpose technology; the relationships between AI, growth, jobs, and inequality; regulatory responses to changes brought on by AI; and the effects of AI on the way economic research is conducted. It explores the economic influence of machine learning, the branch of computational statistics that has driven much of the recent excitement around AI, as well as the economic impact of robotics and automation and the potential economic consequences of a still-hypothetical artificial general intelligence. The volume provides frameworks for understanding the economic impact of AI and identifies a number of open research questions.

Contributors:
Daron Acemoglu, Massachusetts Institute of Technology
Philippe Aghion, Collège de France
Ajay Agrawal, University of Toronto
Susan Athey, Stanford University
James Bessen, Boston University School of Law
Erik Brynjolfsson, MIT Sloan School of Management
Colin F. Camerer, California Institute of Technology
Judith Chevalier, Yale School of Management
Iain M. Cockburn, Boston University
Tyler Cowen, George Mason University
Jason Furman, Harvard Kennedy School
Patrick Francois, University of British Columbia 
Alberto Galasso, University of Toronto
Joshua Gans, University of Toronto
Avi Goldfarb, University of Toronto
Austan Goolsbee, University of Chicago Booth School of Business
Rebecca Henderson, Harvard Business School
Ginger Zhe Jin, University of Maryland
Benjamin F. Jones, Northwestern University
Charles I. Jones, Stanford University
Daniel Kahneman, Princeton University
Anton Korinek, Johns Hopkins University
Mara Lederman, University of Toronto
Hong Luo, Harvard Business School
John McHale, National University of Ireland
Paul R. Milgrom, Stanford University
Matthew Mitchell, University of Toronto
Alexander Oettl, Georgia Institute of Technology
Andrea Prat, Columbia Business School
Manav Raj, New York University
Pascual Restrepo, Boston University
Daniel Rock, MIT Sloan School of Management
Jeffrey D. Sachs, Columbia University
Robert Seamans, New York University
Scott Stern, MIT Sloan School of Management
Betsey Stevenson, University of Michigan
Joseph E. Stiglitz. Columbia University
Chad Syverson, University of Chicago Booth School of Business
Matt Taddy, University of Chicago Booth School of Business
Steven Tadelis, University of California, Berkeley
Manuel Trajtenberg, Tel Aviv University
Daniel Trefler, University of Toronto
Catherine Tucker, MIT Sloan School of Management
Hal Varian, University of California, Berkeley

“"The book is a timely contribution to our understanding of how artificial intelligence (AI) as a technology may evolve and how it may exert impacts on the economy and the ways we live, work and think. It convenes 30 leading economists and asks them to foresee how AI will change specific aspects of the economy in which they have expertise, thus scoping out a research agenda for the next 20 years into the economics of AI. This is as if these economists were back to1995 when the internet was about to begin transforming industries and gathered to debate about what would have happened to economic research into that revolution. This approach of amassing forward-looking perspectives of leading economists is unique amongst books on AI and the economy and is therefore highly valuable. Businesses, public policymakers and researchers can all find useful insights from this book."”

-- "Economic Record"
"Likely to remain the leading reference in this field for years to come... The book rightly calls itself 'an agenda' as the rapid increase in, and development of, AI applications will require constant reassessment of the implications, costs and benefits. The book does set an agenda and across a large range of issues."-- "Prometheus"

Ajay Agrawal is the Peter Munk Professor of Entrepreneurship at the Rotman School of Management, University of Toronto, and 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.

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