Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction

27 Pages Posted: 4 Mar 2019 Last revised: 10 Apr 2019

See all articles by Ajay Agrawal

Ajay Agrawal

University of Toronto - Rotman School of Management; National Bureau of Economic Research (NBER)

Joshua S. Gans

University of Toronto - Rotman School of Management; NBER

Avi Goldfarb

University of Toronto - Rotman School of Management

Multiple version iconThere are 2 versions of this paper

Date Written: February 2019

Abstract

Recent advances in artificial intelligence are primarily driven by machine learning, a prediction technology. Prediction is useful because it is an input into decision-making. In order to appreciate the impact of artificial intelligence on jobs, it is important to understand the relative roles of prediction and decision tasks. We describe and provide examples of how artificial intelligence will affect labor, emphasizing differences between when automating prediction leads to automating decisions versus enhancing decision-making by humans.

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Suggested Citation

Agrawal, Ajay and Gans, Joshua S. and Goldfarb, Avi, Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction (February 2019). NBER Working Paper No. w25619. Available at SSRN: https://ssrn.com/abstract=3346265

Ajay Agrawal (Contact Author)

University of Toronto - Rotman School of Management ( email )

105 St. George Street
Toronto, Ontario M5S 3E6 M5S1S4
Canada

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
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Joshua S. Gans

University of Toronto - Rotman School of Management ( email )

Canada

HOME PAGE: http://www.joshuagans.com

NBER ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Avi Goldfarb

University of Toronto - Rotman School of Management ( email )

105 St. George Street
Toronto, Ontario M5S 3E6 M5S1S4
Canada
416-946-8604 (Phone)
416-978-5433 (Fax)

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