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

Author

Listed:
  • Kanazawa, Kyogo

    (University of Tokyo)

  • Kawaguchi, Daiji

    (University of Tokyo)

  • Shigeoka, Hitoshi

    (Simon Fraser University)

  • Watanabe, Yasutora

    (University of Tokyo)

Abstract

We examine the impact of Articial 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

  • Kanazawa, Kyogo & Kawaguchi, Daiji & Shigeoka, Hitoshi & Watanabe, Yasutora, 2022. "AI, Skill, and Productivity: The Case of Taxi Drivers," IZA Discussion Papers 15677, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp15677
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    Keywords

    artificial intelligence; skill; productivity; taxi-drivers; prediction; demand forecasting; machine learning;
    All these keywords.

    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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