How Does AI Improve Human Decision-Making? Evidence from the AI-Powered Go Program

61 Pages Posted: 28 Jul 2021 Last revised: 13 May 2022

See all articles by Sukwoong Choi

Sukwoong Choi

MIT Sloan School of Management

Namil Kim

School of Management, Harbin Institute of Technology

Junsik Kim

Harvard University

Hyo Kang

Marshall School of Business, University of Southern California

Date Written: April 2022

Abstract

Firms increasingly utilize AI to assist or replace human tasks. However, AI can also train humans and make them better. We study how the AI’s instructional role improves human decision-making in the professional Go games where an AI-powered Go program (APG) unexpectedly surpassed the best human player, surpassing the best human knowledge and skill accumulated over thousands of years. To isolate the learning-from-AI effect, we compare the quality of human moves to that of AI’s superior solutions, before and after the initial public release of an APG. Our analysis of 750,990 moves in 25,033 games suggests that APG’s training significantly improved the players’ move quality—reducing the number of errors and the magnitude of the most critical mistake. The improvement is most prominent in the early stage of a game when uncertainty and unexpectedness are higher. Further, younger players benefit more than older players, suggesting generational inequality in learning from AI.

Keywords: Artificial Intelligence (AI), Technology adoption, Decision-making, Human capital, Professional Go players, AI adoption inequality

JEL Classification: D81, J24, M12, O15, O33

Suggested Citation

Choi, Sukwoong and Kim, Namil and Kim, Junsik and Kang, Hyo, How Does AI Improve Human Decision-Making? Evidence from the AI-Powered Go Program (April 2022). USC Marshall School of Business Research Paper Sponsored by iORB, No. Forthcoming, Available at SSRN: https://ssrn.com/abstract=3893835 or http://dx.doi.org/10.2139/ssrn.3893835

Sukwoong Choi

MIT Sloan School of Management ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Namil Kim (Contact Author)

School of Management, Harbin Institute of Technology ( email )

92 West Dazhi Street
Nan Gang District
Harbin, heilongjiang 150001
China

HOME PAGE: http://namilkim.github.io

Junsik Kim

Harvard University ( email )

150 western Ave.
2.423 SEC Harvard
Boston, MA 02134
United States

HOME PAGE: http://https://sites.google.com/site/jskimcv/

Hyo Kang

Marshall School of Business, University of Southern California ( email )

701 Exposition Blvd
Los Angeles, CA California 90089
United States

HOME PAGE: http://hyokang.com

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