Exploring the Impact of Artificial Intelligence: Prediction Versus Judgment

17 Pages Posted: 24 May 2018

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: May 12, 2018

Abstract

Based on recent developments in the field of artificial intelligence (AI), we examine what type of human labor will be a substitute versus a complement to emerging technologies. We argue that these recent developments reduce the costs of providing a particular set of tasks – prediction tasks. Prediction about uncertain states of the world is an input into decision-making. We show that prediction allows riskier decisions to be taken and this is its impact on observed productivity although it could also increase the variance of outcomes as well. We consider the role of human judgment in decision-making as prediction technology improves. Judgment is exercised when the objective function for a particular set of decisions cannot be described (i.e., coded). However, we demonstrate that better prediction impacts the returns to different types of judgment in opposite ways. Hence, not all human judgment will be a complement to AI. Finally, we show that humans will delegate some decisions to machines even when the decision would be superior with human input.

Keywords: artificial intelligence, prediction, judgment, authority, delegation, bounded rationality

JEL Classification: D81

Suggested Citation

Agrawal, Ajay and Gans, Joshua S. and Goldfarb, Avi, Exploring the Impact of Artificial Intelligence: Prediction Versus Judgment (May 12, 2018). Rotman School of Management Working Paper No. 3177467. Available at SSRN: https://ssrn.com/abstract=3177467 or http://dx.doi.org/10.2139/ssrn.3177467

Ajay Agrawal

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
United States

Joshua S. Gans (Contact Author)

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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