The Economics of Artificial Intelligence
The Economics of Artificial Intelligence provides a powerful insight on the potential of Artificial Intelligence to influence productivity, growth, inequality, market power, innovation, and employment. With frameworks for understanding the economic impact of AI and a portion of open research questions, it also explores the economic influence of machine learning, and the economic impact of robotics and automation. It also provides coverage on AI as a general purpose technology; the relationship between AI, growth, jobs, and inequality; regulatory responses to changes brought by AI; and the effects of AI on the way economic research is conducted. The Economics of Artificial Intelligence tackles the impact of the potential economic consequences of all still-hypothetical artificial general intelligence.
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
Table of Contents
I. AI as a GPT
1. Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics
2. The Technological Elements of Artificial Intelligence
3. Prediction, Judgment, and Complexity: A Theory of Decision-Making and Artificial Intelligence
4. The Impact of Artificial Intelligence on Innovation: An Exploratory Analysis
5. Finding Needles in Haystacks: Artificial Intelligence and Recombinant Growth
6. Artificial Intelligence as the Next GPT: A Political-Economy Perspective
II. Growth, Jobs, and Inequality
7. Artificial Intelligence, Income, Employment, and Meaning
8. Artificial Intelligence, Automation, and Work
9. Artificial Intelligence and Economic Growth
10. Artificial Intelligence and Jobs: The Role of Demand
11. Public Policy in an AI Economy
12. Should We Be Reassured If Automation in the Future Looks Like Automation in the Past?
13. R&D, Structural Transformation, and the Distribution of Income
14. Artificial Intelligence and Its Implications for Income Distribution and Unemployment
15. Neglected Open Questions in the Economics of Artificial Intelligence
III. Machine Learning and Regulation
16. Artificial Intelligence, Economics, and Industrial Organization
17. Privacy, Algorithms, and Artificial Intelligence
18. Artificial Intelligence and Consumer Privacy
19. Artificial Intelligence and International Trade
20. Punishing Robots: Issues in the Economics of Tort Liability and Innovation in Artificial Intelligence
IV. Machine Learning and Economics
21. The Impact of Machine Learning on Economics
22. Artificial Intelligence, Labor, Productivity, and the Need for Firm-Level Data
23. How Artificial Intelligence and Machine Learning Can Impact Market Design
24. Artificial Intelligence and Behavioral Economics