Exploring the Impact of Artificial Intelligence: Prediction versus Judgment

Ajay Agrawal, Joshua Gans and Avi Goldfarb

No 24626, NBER Working Papers from National Bureau of Economic Research, Inc

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.

JEL-codes: D81 O3 (search for similar items in EconPapers)
Date: 2018-05
New Economics Papers: this item is included in nep-big
Note: PR
References: Add references at CitEc
Citations: View citations in EconPapers (6)

Published as Ajay Agrawal & Joshua S. Gans & Avi Goldfarb, 2019. "Exploring the Impact of Artificial Intelligence: Prediction versus Judgment," Information Economics and Policy, .

Downloads: (external link)
http://www.nber.org/papers/w24626.pdf (application/pdf)

Related works:
Journal Article: Exploring the impact of artificial Intelligence: Prediction versus judgment (2019)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nbr:nberwo:24626

Ordering information: This working paper can be ordered from
http://www.nber.org/papers/w24626

Access Statistics for this paper

More papers in NBER Working Papers from National Bureau of Economic Research, Inc National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by ().