TY  - JOUR
AU  - Aghion, Philippe
AU  - Jones, Benjamin F
AU  - Jones, Charles I
TI  - Artificial Intelligence and Economic Growth
JF  - National Bureau of Economic Research Working Paper Series
VL  - No. 23928
PY  - 2017
Y2  - October 2017
DO  - 10.3386/w23928
UR  - http://www.nber.org/papers/w23928
L1  - http://www.nber.org/papers/w23928.pdf
N1  - Author contact info:
Philippe Aghion
College de France
3 Rue D'Ulm
75005 Paris
FRANCE
E-Mail: p.aghion@lse.ac.uk

Benjamin Jones
Northwestern University
Kellogg School of Management
Department of Management and Strategy
2211 Campus Drive
Evanston, IL  60208
Tel: 847/491-3177
Fax: 847/467-1777
E-Mail: bjones@kellogg.northwestern.edu

Charles I. Jones
Graduate School of Business
Stanford University
655 Knight Way
Stanford, CA 94305-4800
Tel: 650/725-9265
Fax: 650/725-0468
E-Mail: chad.jones@stanford.edu
M1  - published as Philippe Aghion, Benjamin F. Jones, Charles I. Jones. "Artificial Intelligence and Economic Growth," in Ajay Agrawal, Joshua Gans, and Avi Goldfarb, editors, "The Economics of Artificial Intelligence: An Agenda" University of Chicago Press (2019)

M3  - presented at "Economics of Artificial Intelligence", September 13-14, 2017
AB  - This paper examines the potential impact of artificial intelligence (A.I.) on economic growth. We model A.I. as the latest form of automation, a broader process dating back more than 200 years. Electricity, internal combustion engines, and semiconductors facilitated automation in the last century, but A.I. now seems poised to automate many tasks once thought to be out of reach, from driving cars to making medical recommendations and beyond. How will this affect economic growth and the division of income between labor and capital? What about the potential emergence of “singularities” and “superintelligence,” concepts that animate many discussions in the machine intelligence community? How will the linkages between A.I. and growth be mediated by firm-level considerations, including organization and market structure? The goal throughout is to refine a set of critical questions about A.I. and economic growth and to contribute to shaping an agenda for the field. One theme that emerges is based on Baumol’s “cost disease” insight: growth may be constrained not by what we are good at but rather by what is essential and yet hard to improve.
ER  -