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Artificial intelligence and economic growth

Author: Philippe Aghion; Benjamin F Jones; Charles I Jones; National Bureau of Economic Research,
Publisher: Cambridge, Mass. : National Bureau of Economic Research, 2017.
Series: Working paper series (National Bureau of Economic Research), no. 23928.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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  Read more...
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Details

Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Philippe Aghion; Benjamin F Jones; Charles I Jones; National Bureau of Economic Research,
OCLC Number: 1006744715
Notes: "October 2017"
Description: 1 online resource (56 pages) : illustrations.
Series Title: Working paper series (National Bureau of Economic Research), no. 23928.
Responsibility: Philippe Aghion, Benjamin F. Jones, Charles I. Jones.

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.

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