AI, Skill, and Productivity: The Case of Taxi Drivers

Kyogo Kanazawa, Daiji Kawaguchi, Hitoshi Shigeoka and Yasutora Watanabe

No 30612, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We examine the impact of Artificial Intelligence (AI) on productivity in the context of taxi drivers. The AI we study assists drivers with finding customers by suggesting routes along which the demand is predicted to be high. We find that AI improves drivers’ productivity by shortening the cruising time, and such gain is accrued only to low-skilled drivers, narrowing the productivity gap between high- and low-skilled drivers by 14%. The result indicates that AI's impact on human labor is more nuanced and complex than a job displacement story, which was the primary focus of existing studies.

JEL-codes: J22 J24 L92 R41 (search for similar items in EconPapers)
Date: 2022-10
New Economics Papers: this item is included in nep-big, nep-eff, nep-hrm and nep-lma
Note: AG LS PR
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Working Paper: AI, Skill, and Productivity: The Case of Taxi Drivers (2022)
Working Paper: AI, Skill, and Productivity: The Case of Taxi Drivers (2022)
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