The Economics of Artificial Intelligence

Description

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. 

About the Editors

Ajay Agrawal is the Peter Munk Professor of Entrepreneurship at the Rotman School of Management, University of Toronto, Canada, and a research associate at the National Bureau of Economic Research (NBER), USA.

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 (with a cross appointment in the Department of Economics), University of Toronto, and a research associate at 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 at the NBER.

Contributors

Ajay Agrawal, Joshua Gans, Avi Goldfarb, Erik Brynjolfsson, Daniel Rock, Chad Syverson, Matt Taddy, Iain M. Cockburn, Rebecca Henderson, Scott Stern, John McHale, Alexander Oettl, Manuel Trajtenberg, Betsey Stevenson, Daron Acemoglu and Pascual Restrepo, Philippe Aghion, Benjamin F. Jones, and Charles I. Jones, James Bessen, Austan Goolsbee, Jason Furman, Jeff rey D. Sachs, Anton Korinek, Joseph E. Stiglitz, Tyler Cowen, Hal Varian, Catherine Tucker, Ginger Zhe Jin, Daniel Trefler, Alberto Galasso, Hong Luo, Susan Athey, Manav Raj, Robert Seamans, Paul R. Milgrom, Steven Tadelis, Colin F. Camerer

Commentators: Rebecca Henderson, Andrea Prat, Matthew Mitchell, Patrick Francois, Judith Chevalier, Mara Lederman, Daniel Kahneman

Table of contents

Acknowledgments xi

Introduction 1

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 23

Erik Brynjolfsson, Daniel Rock, and Chad Syverson

Comment: Rebecca Henderson

2. The Technological Elements of Artificial Intelligence 61

Matt Taddy

3. Prediction, Judgment, and Complexity: A Theory of Decision-Making and Artificial Intelligence 89

Ajay Agrawal, Joshua Gans, and Avi Goldfarb

Comment: Andrea Prat

4. The Impact of Artificial Intelligence on Innovation: An Exploratory Analysis 115

Iain M. Cockburn, Rebecca Henderson, and Scott Stern

Comment: Matthew Mitchell

5. Finding Needles in Haystacks: Artificial Intelligence and Recombinant Growth 149

Ajay Agrawal, John McHale, and Alexander Oettl

6. Artificial Intelligence as the Next GPT: A Political-Economy Perspective 175

Manuel Trajtenberg

 II. Growth, Jobs, and Inequality

7. Artificial Intelligence, Income, Employment, and Meaning 189

Betsey Stevenson

8. Artificial Intelligence, Automation, and Work 197

Daron Acemoglu and Pascual Restrepo

9. Artificial Intelligence and Economic Growth 237

Philippe Aghion, Benjamin F. Jones, and Charles I. Jones

Comment: Patrick Francois

10. Artificial Intelligence and Jobs: The Role of Demand 291

James Bessen

11. Public Policy in an AI Economy 309

Austan Goolsbee

12. Should We Be Reassured If Automation in the Future Looks Like Automation in the Past? 317

Jason Furman

13. R&D, Structural Transformation, and the Distribution of Income 329

Jeff rey D. Sachs

14. Artificial Intelligence and Its Implications for Income Distribution and Unemployment 349

Anton Korinek and Joseph E. Stiglitz

15. Neglected Open Questions in the Economics of Artifi cial Intelligence 391

Tyler Cowen

III. Machine Learning and Regulation

16. Artificial Intelligence, Economics, and Industrial Organization 399

Hal Varian

Comment: Judith Chevalier

17. Privacy, Algorithms, and Artificial Intelligence 423

Catherine Tucker

18. Artificial Intelligence and Consumer Privacy 439

Ginger Zhe Jin

19. Artificial Intelligence and International Trade 463

Avi Goldfarb and Daniel Trefler

20. Punishing Robots: Issues in the Economics of Tort Liability and Innovation in Artificial Intelligence 493

Alberto Galasso and Hong Luo

IV. Machine Learning and Economics

1. The Impact of Machine Learning on Economics 507

Susan Athey

Comment: Mara Lederman

22. Artificial Intelligence, Labor, Productivity, and the Need for Firm-Level Data 553

Manav Raj and Robert Seamans

23. How Artificial Intelligence and Machine Learning Can Impact Market Design 567

Paul R. Milgrom and Steven Tadelis

24. Artificial Intelligence and Behavioral Economics 587

Colin F. Camerer

Comment: Daniel Kahneman

Contributors 611

Author Index 615

Subject Index 625