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The Economics of Artificial Intelligence – An Agenda - Chicago Scholarship Online
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The Economics of Artificial Intelligence: An Agenda

Ajay Agrawal, Joshua Gans, and Avi Goldfarb


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 econ ... More

Keywords: artificial intelligence, machine learning, economics of innovation, general purpose technologies, regulation, inequality, productivity

Bibliographic Information

Print publication date: 2019 Print ISBN-13: 9780226613338
Published to Chicago Scholarship Online: January 2020 DOI:10.7208/chicago/9780226613475.001.0001


Affiliations are at time of print publication.

Ajay Agrawal, editor
University of Toronto

Joshua Gans, editor
University of Toronto

Avi Goldfarb, editor
University of Toronto

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Ajay Agrawal, Joshua Gans, and Avi Goldfarb

I AI as a GPT

1 Artificial Intelligence and the Modern Productivity Paradox

Erik Brynjolfsson, Daniel Rock, and Chad Syverson

3 Prediction, Judgment, and Complexity

Ajay Agrawal, Joshua Gans, and Avi Goldfarb

4 The Impact of Artificial Intelligence on Innovation

Iain M. Cockburn, Rebecca Henderson, and Scott Stern

5 Finding Needles in Haystacks

Ajay Agrawal, John McHale, and Alexander Oettl

II Growth, Jobs, and Inequality

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

III Machine Learning and Regulation

19 Artificial Intelligence and International Trade

Avi Goldfarb and Daniel Trefler

IV Machine Learning and Economics