Artificial Intelligence and Economic Growth
Philippe Aghiona b c d e, Benjamin F. Jonesb c d e f, Charles I. Jonesb c d e g
- aCollege de France 3 Rue D' Ulm 75005 Paris FRANCE
- bCollege de France 3 Rue D'Ulm 75005 Paris FRANCE
- cGraduate School of Business Stanford University 655 Knight Way Stanford, CA 94305-4800
- dNATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge, MA 02138
- eNorthwestern University Kellogg School of Management Department of Management and Strategy 2001 Sheridan Road Evanston, IL 60208 and
- fNorthwestern University Kellogg School of Management Department of Management and Strategy 2001 Sheridan Road Evanston , IL 60208 and
- gGraduate School of Business Stanford University 655 Knight Way Stanford , CA 94305-4800 and
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Abstract
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.
TL;DRThe potential impact of artificial intelligence on economic growth is examined, based on Baumol’s “cost disease” insight: growth may be constrained not by what the authors are good at but rather by what is essential and yet hard to improve. (Semantic Scholar)