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

Sukwoong Choi, Hyo Kang, Namil Kim and Junsik Kim

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Abstract: We study how humans learn from AI, exploiting an introduction of an AI-powered Go program (APG) that unexpectedly outperformed the best professional player. We compare the move quality of professional players to that of APG's superior solutions around its public release. Our analysis of 749,190 moves demonstrates significant improvements in players' move quality, accompanied by decreased number and magnitude of errors. The effect is pronounced in the early stages of the game where uncertainty is highest. In addition, younger players and those in AI-exposed countries experience greater improvement, suggesting potential inequality in learning from AI. Further, while players of all levels learn, less skilled players derive higher marginal benefits. These findings have implications for managers seeking to adopt and utilize AI effectively within their organizations.

Date: 2023-10
New Economics Papers: this item is included in nep-ain, nep-big, nep-cmp and nep-spo
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Handle: RePEc:arx:papers:2310.08704