The Economics of Artificial Intelligence: An Agenda

Published by University of Chicago Press 2019

The Economics of Artificial Intelligence

An Agenda

Edited by: Ajay Agrawal , Joshua Gans and Avi Goldfarb

In the series National Bureau of Economic Research Conference Report

https://doi.org/10.7208/9780226613475

Overview
Contents

About this book

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

Author / Editor information

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.

Reviews

"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

Topics

Frontmatter Publicly Available Download PDF	i
Contents Publicly Available Download PDF	vii
Acknowledgments Publicly Available Download PDF	xi
Introduction Ajay Agrawal, Joshua Gans and Avi Goldfarb Requires Authentication Unlicensed Licensed Download PDF	1
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 Requires Authentication Unlicensed Licensed Download PDF	23
2. The Technological Elements of Artificial Intelligence Matt Taddy Requires Authentication Unlicensed Licensed Download PDF	61
3. Prediction, Judgment, and Complexity: A Theory of Decision-Making and Artificial Intelligence Ajay Agrawal, Joshua Gans and Avi Goldfarb Requires Authentication Unlicensed Licensed Download PDF	89
4. The Impact of Artificial Intelligence on Innovation: An Exploratory Analysis Iain M. Cockburn, Rebecca Henderson and Scott Stern Requires Authentication Unlicensed Licensed Download PDF	115
5. Finding Needles in Haystacks: Artificial Intelligence and Recombinant Growth Ajay Agrawal, John McHale and Alexander Oettl Requires Authentication Unlicensed Licensed Download PDF	149
6. Artificial Intelligence as the Next GPT: A Political-Economy Perspective Manuel Trajtenberg Requires Authentication Unlicensed Licensed Download PDF	175
II. Growth, Jobs, and Inequality
7. Artificial Intelligence, Income, Employment, and Meaning Betsey Stevenson Requires Authentication Unlicensed Licensed Download PDF	189
8. Artificial Intelligence, Automation, and Work Daron Acemoglu and Pascual Restrepo Requires Authentication Unlicensed Licensed Download PDF	197
9. Artificial Intelligence and Economic Growth Philippe Aghion, Benjamin F. Jones and Charles I. Jones Requires Authentication Unlicensed Licensed Download PDF	237
10. Artificial Intelligence and Jobs: The Role of Demand James Bessen Requires Authentication Unlicensed Licensed Download PDF	291
11. Public Policy in an AI Economy Austan Goolsbee Requires Authentication Unlicensed Licensed Download PDF	309
12. Should We Be Reassured If Automation in the Future Looks Like Automation in the Past? Jason Furman Requires Authentication Unlicensed Licensed Download PDF	317
13. R&D, Structural Transformation, and the Distribution of Income Jeffrey D. Sachs Requires Authentication Unlicensed Licensed Download PDF	329
14. Artificial Intelligence and Its Implications for Income Distribution and Unemployment Anton Korinek and Joseph E. Stiglitz Requires Authentication Unlicensed Licensed Download PDF	349
15. Neglected Open Questions in the Economics of Artificial Intelligence Tyler Cowen Requires Authentication Unlicensed Licensed Download PDF	391
III. Machine Learning and Regulation
16. Artificial Intelligence, Economics, and Industrial Organization Hal Varian Requires Authentication Unlicensed Licensed Download PDF	399
17. Privacy, Algorithms, and Artificial Intelligence Catherine Tucker Requires Authentication Unlicensed Licensed Download PDF	423
18. Artificial Intelligence and Consumer Privacy Ginger Zhe Jin Requires Authentication Unlicensed Licensed Download PDF	439
19. Artificial Intelligence and International Trade Avi Goldfarb and Daniel Trefler Requires Authentication Unlicensed Licensed Download PDF	463
20. Punishing Robots: Issues in the Economics of Tort Liability and Innovation in Artificial Intelligence Alberto Galasso and Hong Luo Requires Authentication Unlicensed Licensed Download PDF	493
IV. Machine Learning and Economics
21. The Impact of Machine Learning on Economics Susan Athey Requires Authentication Unlicensed Licensed Download PDF	507
22. Artificial Intelligence, Labor, Productivity, and the Need for Firm-Level Data Manav Raj and Robert Seamans Requires Authentication Unlicensed Licensed Download PDF	553
23. How Artificial Intelligence and Machine Learning Can Impact Market Design Paul R. Milgrom and Steven Tadelis Requires Authentication Unlicensed Licensed Download PDF	567
24. Artificial Intelligence and Behavioral Economics Colin F. Camerer Requires Authentication Unlicensed Licensed Download PDF	587
Contributors Requires Authentication Unlicensed Licensed Download PDF	611
Author Index Requires Authentication Unlicensed Licensed Download PDF	615
Subject Index Requires Authentication Unlicensed Licensed Download PDF	625

Language: English
Publisher: University of Chicago Press
Audience: Professional and scholarly;
Pages
- Main content: 648
Illustrations
- Other: 74 line drawings, 21 tables
Keywords: artificial intelligence; machine learning; economics of innovation; general purpose technologies; regulation; inequality; productivity

eBook

Published: June 7, 2019
ISBN: 9780226613475