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

Author

Listed:
  • Kyogo Kanazawa

    (Faculty of Economics, The University of Tokyo)

  • Daiji Kawaguchi

    (Faculty of Economics, The University of Tokyo, RIETI and IZA)

  • Hitoshi Shigeoka

    (Faculty of Economics, The University of Tokyo, Simon Fraser University, IZA, and NBER)

  • Yasutora Watanabe

    (Faculty of Economics, The University of Tokyo)

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.

Suggested Citation

  • Kyogo Kanazawa & Daiji Kawaguchi & Hitoshi Shigeoka & Yasutora Watanabe, 2022. "AI, Skill, and Productivity: The Case of Taxi Drivers," CIRJE F-Series CIRJE-F-1202, CIRJE, Faculty of Economics, University of Tokyo.
    • Handle: RePEc:tky:fseres:2022cf1202
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    JEL classification:

    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • L92 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Railroads and Other Surface Transportation
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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