The Economics of Artificial Intelligence: An Agenda (National Bureau of Economic Research Conference Report)

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 Contents Acknowledgments Introduction / Ajay Agrawal, Joshua Gans, and Avi Goldfarb I. AI as a GPT 1. Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics / Erik Brynjolfsson, Daniel Rock, and Chad Syverson, Comment: Rebecca Henderson 2. The Technological Elements of Artificial Intelligence / Matt Taddy 3. Prediction, Judgment, and Complexity: A Theory of Decision-Making and Artificial Intelligence / Ajay Agrawal, Joshua Gans, and Avi Goldfarb, Comment: Andrea Prat 4. The Impact of Artificial Intelligence on Innovation: An Exploratory Analysis / Iain M. Cockburn, Rebecca Henderson, and Scott Stern, Comment: Matthew Mitchell 5. Finding Needles in Haystacks: Artificial Intelligence and Recombinant Growth / Ajay Agrawal, John McHale, and Alexander Oettl 6. Artificial Intelligence as the Next GPT: A Political-Economy Perspective / Manuel Trajtenberg II. Growth, Jobs, and Inequality 7. Artificial Intelligence, Income, Employment, and Meaning / Betsey Stevenson 8. Artificial Intelligence, Automation, and Work / Daron Acemoglu and Pascual Restrepo 9. Artificial Intelligence and Economic Growth / Philippe Aghion, Benjamin F. Jones, and Charles I. Jones, Comment: Patrick Francois 10. Artificial Intelligence and Jobs: The Role of Demand / James Bessen 11. Public Policy in an AI Economy / Austan Goolsbee 12. Should We Be Reassured If Automation in the Future Looks Like Automation in the Past? / Jason Furman 13. R&D, Structural Transformation, and the Distribution of Income / Jeffrey D. Sachs 14. Artificial Intelligence and Its Implications for Income Distribution and Unemployment / Anton Korinek and Joseph E. Stiglitz 15. Neglected Open Questions in the Economics of Artificial Intelligence / Tyler Cowen III. Machine Learning and Regulation 16. Artificial Intelligence, Economics, and Industrial Organization / Hal Varian, Comment: Judith Chevalier 17. Privacy, Algorithms, and Artifi cial Intelligence / Catherine Tucker 18. Artificial Intelligence and Consumer Privacy / Ginger Zhe Jin 19. Artificial Intelligence and International Trade / Avi Goldfarb and Daniel Trefler 20. Punishing Robots: Issues in the Economics of Tort Liability and Innovation in Artificial Intelligence / Alberto Galasso and Hong Luo IV. Machine Learning and Economics 21. The Impact of Machine Learning on Economics / Susan Athey, Comment: Mara Lederman 22. Artificial Intelligence, Labor, Productivity, and the Need for Firm-Level Data / Manav Raj and Robert Seamans 23. How Artificial Intelligence and Machine Learning Can Impact Market Design / Paul R. Milgrom and Steven Tadelis 24. Artificial Intelligence and Behavioral Economics / Colin F. Camerer, Comment: Daniel Kahneman Contributors Author Index Subject Index Recent advances in artificial intelligence (AI) highlight its potential to affect productivity, growth, inequality, market power, innovation, and employment. In September 2017, the National Bureau of Economic Research held its first conference on the Economics of AI in Toronto. The purpose of the conference and associated volume is to set the research agenda for economists working on AI. The focus of the volume is on the economic impact of machine learning, a branch of computational statistics that has driven the recent excitement around AI. The volume also highlights key questions on the economic impact of robotics and automation, as well as the potential economic consequences of a still-hypothetical artificial general intelligence