IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v72y2026i2p1376-1388.html

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

Author

Listed:
  • Kyogo Kanazawa

    (University of Tokyo, Tokyo 113-0033, Japan; and Yokohama National University, Yokohama, Kanagawa 240-8501, Japan)

  • Daiji Kawaguchi

    (University of Tokyo, Tokyo 113-0033, Japan; and Research Institute of Economy, Trade and Industry (RIETI), Tokyo 100-8901, Japan; and IZA, 53113 Bonn, Germany)

  • Hitoshi Shigeoka

    (University of Tokyo, Tokyo 113-0033, Japan; and IZA, 53113 Bonn, Germany; and Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada; and NBER, Cambridge, Massachusetts 02138)

  • Yasutora Watanabe

    (University of Tokyo, Tokyo 113-0033, Japan)

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 this gain is accrued only to low-skilled drivers, narrowing the productivity gap between high- and low-skilled drivers by 13.4%. This case study provides evidence that AI and skill are indeed substitutes, offering direct support for the underlying assumption of recent projection exercises regarding job displacement by AI.

Suggested Citation

  • Kyogo Kanazawa & Daiji Kawaguchi & Hitoshi Shigeoka & Yasutora Watanabe, 2026. "AI, Skill, and Productivity: The Case of Taxi Drivers," Management Science, INFORMS, vol. 72(2), pages 1376-1388, February.
    • Handle: RePEc:inm:ormnsc:v:72:y:2026:i:2:p:1376-1388
    DOI: 10.1287/mnsc.2023.01631
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.2023.01631
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.2023.01631?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    2. Atack, Jeremy & Margo, Robert A. & Rhode, Paul W., 2024. "De-skilling: Evidence from late nineteenth century American manufacturing," Explorations in Economic History, Elsevier, vol. 91(C).
    3. Colin Camerer & Linda Babcock & George Loewenstein & Richard Thaler, 1997. "Labor Supply of New York City Cabdrivers: One Day at a Time," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 112(2), pages 407-441.
    4. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2009. "Dealing with limited overlap in estimation of average treatment effects," Biometrika, Biometrika Trust, vol. 96(1), pages 187-199.
    5. Joshua D. Angrist & Sydnee Caldwell & Jonathan V. Hall, 2021. "Uber versus Taxi: A Driver's Eye View," American Economic Journal: Applied Economics, American Economic Association, vol. 13(3), pages 272-308, July.
    6. Daron Acemoglu & David Autor & Jonathon Hazell & Pascual Restrepo, 2022. "Artificial Intelligence and Jobs: Evidence from Online Vacancies," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 293-340.
    7. David H. Autor & Lawrence F. Katz & Melissa S. Kearney, 2008. "Trends in U.S. Wage Inequality: Revising the Revisionists," The Review of Economics and Statistics, MIT Press, vol. 90(2), pages 300-323, May.
    8. Kyogo Kanazawa & Daiji Kawaguchi & Hitoshi Shigeoka & Yasutora Watanabe, 2026. "AI, Skill, and Productivity: The Case of Taxi Drivers," Management Science, INFORMS, vol. 72(2), pages 1376-1388, February.
    9. Evan Rawley & Timothy S. Simcoe, 2013. "Information Technology, Productivity, and Asset Ownership: Evidence from Taxicab Fleets," Organization Science, INFORMS, vol. 24(3), pages 831-845, June.
    10. Henry S. Farber, 2008. "Reference-Dependent Preferences and Labor Supply: The Case of New York City Taxi Drivers," American Economic Review, American Economic Association, vol. 98(3), pages 1069-1082, June.
    11. Guido W. Imbens, 2015. "Matching Methods in Practice: Three Examples," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 373-419.
    12. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The Skill Content of Recent Technological Change: An Empirical Exploration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(4), pages 1279-1333.
    13. Jeanne Lafortune & Ethan Lewis & José Tessada, 2019. "People and Machines: A Look at the Evolving Relationship between Capital and Skill in Manufacturing, 1860–1930, Using Immigration Shocks," The Review of Economics and Statistics, MIT Press, vol. 101(1), pages 30-43, March.
    14. Erik Brynjolfsson & Danielle Li & Lindsey Raymond, 2025. "Generative AI at Work," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 140(2), pages 889-942.
    15. John Gibson & David McKenzie, 2014. "The Development Impact of a Best Practice Seasonal Worker Policy," The Review of Economics and Statistics, MIT Press, vol. 96(2), pages 229-243, May.
    16. Ali Merali, 2024. "Scaling Laws for Economic Productivity: Experimental Evidence in LLM-Assisted Translation," Papers 2409.02391, arXiv.org, revised Dec 2024.
    17. Janet Currie & Reed Walker, 2011. "Traffic Congestion and Infant Health: Evidence from E-ZPass," American Economic Journal: Applied Economics, American Economic Association, vol. 3(1), pages 65-90, January.
    18. Goldin, Claudia & Sokoloff, Kenneth, 1982. "Women, Children, and Industrialization in the Early Republic: Evidence from the Manufacturing Censuses," The Journal of Economic History, Cambridge University Press, vol. 42(4), pages 741-774, December.
    19. Meng Liu & Erik Brynjolfsson & Jason Dowlatabadi, 2021. "Do Digital Platforms Reduce Moral Hazard? The Case of Uber and Taxis," Management Science, INFORMS, vol. 67(8), pages 4665-4685, August.
    20. Mark Doms & Timothy Dunne & Kenneth R. Troske, 1997. "Workers, Wages, and Technology," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 112(1), pages 253-290.
    21. Ann Bartel & Casey Ichniowski & Kathryn Shaw, 2007. "How Does Information Technology Affect Productivity? Plant-Level Comparisons of Product Innovation, Process Improvement, and Worker Skills," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(4), pages 1721-1758.
    22. Babina, Tania & Fedyk, Anastassia & He, Alex & Hodson, James, 2024. "Artificial intelligence, firm growth, and product innovation," Journal of Financial Economics, Elsevier, vol. 151(C).
    23. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    24. Dieterle, Steven G. & Snell, Andy, 2016. "A simple diagnostic to investigate instrument validity and heterogeneous effects when using a single instrument," Labour Economics, Elsevier, vol. 42(C), pages 76-86.
    25. Henry S. Farber, 2005. "Is Tomorrow Another Day? The Labor Supply of New York City Cabdrivers," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 46-82, February.
    26. Kareem Haggag & Brian McManus & Giovanni Paci, 2017. "Learning by Driving: Productivity Improvements by New York City Taxi Drivers," American Economic Journal: Applied Economics, American Economic Association, vol. 9(1), pages 70-95, January.
    27. George P. Baker & Thomas N. Hubbard, 2004. "Contractibility and Asset Ownership: On-Board Computers and Governance in U. S. Trucking," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(4), pages 1443-1479.
    28. David Deming & Lisa B. Kahn, 2018. "Skill Requirements across Firms and Labor Markets: Evidence from Job Postings for Professionals," Journal of Labor Economics, University of Chicago Press, vol. 36(S1), pages 337-369.
    29. Alekseeva, Liudmila & Azar, José & Giné, Mireia & Samila, Sampsa & Taska, Bledi, 2021. "The demand for AI skills in the labor market," Labour Economics, Elsevier, vol. 71(C).
    30. Claudia Goldin & Lawrence F. Katz, 1998. "The Origins of Technology-Skill Complementarity," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(3), pages 693-732.
    31. Daron Acemoglu & Pascual Restrepo, 2022. "Tasks, Automation, and the Rise in U.S. Wage Inequality," Econometrica, Econometric Society, vol. 90(5), pages 1973-2016, September.
    32. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue nov.
    33. George P. Baker & Thomas N. Hubbard, 2003. "Make Versus Buy in Trucking: Asset Ownership, Job Design, and Information," American Economic Review, American Economic Association, vol. 93(3), pages 551-572, June.
    34. David H. Autor & Lawrence F. Katz & Alan B. Krueger, 1998. "Computing Inequality: Have Computers Changed the Labor Market?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(4), pages 1169-1213.
    35. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    36. Jane Humphries, 2013. "Childhood and child labour in the British industrial revolution," Economic History Review, Economic History Society, vol. 66(2), pages 395-418, May.
    37. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jin Kim & Shane Schweitzer & David De Cremer & Christoph Riedl, 2025. "The AI Penalty: People Reduce Compensation for Workers Who Use AI," Papers 2501.13228, arXiv.org, revised Mar 2026.
    2. Ilse Lindenlaub & Ryungha Oh & Mar’a Alejandra Rodr’guez Vega & Laura Veldkamp, 2026. "Beyond Exposure: Predicting AI Adoption Based On Comparative Advantage," Cowles Foundation Discussion Papers 2532, Cowles Foundation for Research in Economics, Yale University.
    3. Bernd Irlenbusch, 2026. "Human Trust in AI: Evidence from Experimental Economics," ECONtribute Discussion Papers Series 417, University of Bonn and University of Cologne, Germany.
    4. Pablo Guerron-Quintana & Tomoaki Mikami & Jaromir Nosal, 2024. "The macroeconomic implications of the Gen-AI economy," Boston College Working Papers in Economics 1080, Boston College Department of Economics.
    5. Lagziel, David & Tsodikovich, Yevgeny, 2025. "Working with AI: An analysis for rational integration," Games and Economic Behavior, Elsevier, vol. 153(C), pages 254-267.
    6. Zhu, Feng & Zou, Wenbo, 2026. "Generative AI adoption in human creative tasks: Experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 242(C).
    7. Kyogo Kanazawa & Daiji Kawaguchi & Hitoshi Shigeoka & Yasutora Watanabe, 2026. "AI, Skill, and Productivity: The Case of Taxi Drivers," Management Science, INFORMS, vol. 72(2), pages 1376-1388, February.
    8. Christoph Riedl & Eric Bogert, 2024. "Who Benefits from AI? Self-Selection, Skill Gap, and the Hidden Costs of AI Feedback," Papers 2409.18660, arXiv.org, revised Apr 2026.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mark Hellsten & Giuseppe Pulito & Sarah Schroeder, 2026. "Automation and the Changing Composition of Skill Demand," RFBerlin Discussion Paper Series 26122, ROCKWOOL Foundation Berlin (RFBerlin).
    2. David Autor & Caroline Chin & Anna Salomons & Bryan Seegmiller, 2024. "New Frontiers: The Origins and Content of New Work, 1940–2018," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 139(3), pages 1399-1465.
    3. Stefania Albanesi & António Dias da Silva & Juan F Jimeno & Ana Lamo & Alena Wabitsch, 2025. "New technologies and jobs in Europe," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 40(121), pages 71-139.
    4. Maarten Goos & Melanie Arntz & Ulrich Zierahn & Terry Gregory & Stephanie Carretero Gomez & Ignacio Gonzalez Vazquez & Koen Jonkers, 2019. "The Impact of Technological Innovation on the Future of Work," JRC Working Papers on Labour, Education and Technology 2019-03, Joint Research Centre.
    5. Gao, Fei & Peng, Benhong & Zhao, Yinyin & Wei, Guo, 2026. "Tech for Good: The employment effects of policy-driven artificial intelligence development," International Review of Economics & Finance, Elsevier, vol. 105(C).
    6. Łukasz Arendt & Eugeniusz Kwiatkowski, 2023. "Kontrowersje wokół wpływu nowoczesnych technologii na zatrudnienie i bezrobocie," Ekonomista, Polskie Towarzystwo Ekonomiczne, issue 2, pages 195-216.
    7. Lyu, Wenjing & Liu, Jin, 2021. "Artificial Intelligence and emerging digital technologies in the energy sector," Applied Energy, Elsevier, vol. 303(C).
    8. Janssen, Simon & Mohrenweiser, Jens, 2018. "The Shelf Life of Incumbent Workers during Accelerating Technological Change: Evidence from a Training Regulation Reform," IZA Discussion Papers 11312, IZA Network @ LISER.
    9. Yoon, Chungeun, 2023. "Technology adoption and jobs: The effects of self-service kiosks in restaurants on labor outcomes," Technology in Society, Elsevier, vol. 74(C).
    10. Benmelech, Efraim & Zator, Michał, 2025. "Robots and firm investment," Journal of Financial Economics, Elsevier, vol. 174(C).
    11. Atack, Jeremy & Margo, Robert A. & Rhode, Paul W., 2024. "De-skilling: Evidence from late nineteenth century American manufacturing," Explorations in Economic History, Elsevier, vol. 91(C).
    12. Ciaschi, Matias & Falcone, Guillermo & Garganta, Santiago & Gasparini, Leonardo & Bertín, Octavio & Ramírez-Leira, Lucía, 2025. "The Potential Distributive Impact of AI-driven Labor Changes in Latin America," IDB Publications (Working Papers) 14253, Inter-American Development Bank.
    13. Jasmine Mondolo, 2022. "The composite link between technological change and employment: A survey of the literature," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 1027-1068, September.
    14. Wu, Yongqiu & Lin, Zhiwei & Zhang, Qingcui & Wang, Wei, 2024. "Artificial intelligence, wage dynamics, and inequality: Empirical evidence from Chinese listed firms," International Review of Economics & Finance, Elsevier, vol. 96(PC).
    15. Falck, Oliver & Heimisch-Roecker, Alexandra & Wiederhold, Simon, 2021. "Returns to ICT skills," Research Policy, Elsevier, vol. 50(7).
    16. David Marguerit, 2025. "Augmenting or Automating Labor? The Effect of AI Development on New Work, Employment, and Wages," Papers 2503.19159, arXiv.org.
    17. Tianyu Fan, 2025. "The Labor Market Incidence of New Technologies," Papers 2504.04047, arXiv.org, revised Nov 2025.
    18. repec:ces:ceswps:_12072 is not listed on IDEAS
    19. Christoph Riedl & Eric Bogert, 2024. "Who Benefits from AI? Self-Selection, Skill Gap, and the Hidden Costs of AI Feedback," Papers 2409.18660, arXiv.org, revised Apr 2026.
    20. David Kunst, 2019. "Deskilling among Manufacturing Production Workers," Tinbergen Institute Discussion Papers 19-050/VI, Tinbergen Institute, revised 30 Dec 2020.
    21. Ana Abeliansky & Klaus Prettner & Ernesto Rodríguez Crespo, 2024. "Climate change and automation: the emission effects of robot adoption," Department of Economics Working Papers wuwp370, Vienna University of Economics and Business, Department of Economics.

    More about this item

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:72:y:2026:i:2:p:1376-1388. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.