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Artificial Intelligence, Automation and Work

Author

Listed:
  • Daron Acemoglu

    (MIT)

  • Pascual Restrepo

    () (Boston University)

Abstract

We summarize a framework for the study of the implications of automation and AI on the demand for labor, wages, and employment. Our task-based framework emphasizes the displacement effect that automation creates as machines and AI replace labor in tasks that it used to perform. This displacement effect tends to reduce the demand for labor and wages. But it is counteracted by a productivity effect, resulting from the cost savings generated by automation, which increase the demand for labor in non-automated tasks. The productivity effect is complemented by additional capital accumulation and the deepening of automation (improvements of existing machinery), both of which further increase the demand for labor. These countervailing effects are incomplete. Even when they are strong, automation in- creases output per worker more than wages and reduce the share of labor in national income. The more powerful countervailing force against automation is the creation of new labor-intensive tasks, which reinstates labor in new activities and tends to in- crease the labor share to counterbalance the impact of automation. Our framework also highlights the constraints and imperfections that slow down the adjustment of the economy and the labor market to automation and weaken the resulting produc- tivity gains from this transformation: a mismatch between the skill requirements of new technologies, and the possibility that automation is being introduced at an excessive rate, possibly at the expense of other productivity-enhancing technologies.

Suggested Citation

  • Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation and Work," Boston University - Department of Economics - The Institute for Economic Development Working Papers Series dp-298, Boston University - Department of Economics.
  • Handle: RePEc:bos:iedwpr:dp-298
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    File URL: http://www.bu.edu/econ/files/2012/11/Artificial-Intelligence-Automation-and-Work.pdf
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    References listed on IDEAS

    as
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    6. Daron Acemoglu & Pascual Restrepo, 2017. "Robots and Jobs: Evidence from US Labor Markets," Boston University - Department of Economics - Working Papers Series dp-297, Boston University - Department of Economics.
    7. repec:nbr:nberch:14015 is not listed on IDEAS
    8. 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.
    9. Daron Acemoglu & Pascual Restrepo, 2017. "Robots and Jobs: Evidence from US Labor Markets," NBER Working Papers 23285, National Bureau of Economic Research, Inc.
    10. Philippe Aghion & Benjamin F. Jones & Charles I. Jones, 2018. "Artificial Intelligence and Economic Growth," NBER Chapters,in: The Economics of Artificial Intelligence: An Agenda, pages 237-282 National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Gregory Casey & Ryo Horii, 2019. "A Multi-factor Uzawa Growth Theorem and Endogenous Capital-Augmenting Technological Change," 2019 Meeting Papers 1458, Society for Economic Dynamics.
    2. David Baqaee & Emmanuel Farhi, 2018. "The Microeconomic Foundations of Aggregate Production Functions," NBER Working Papers 25293, National Bureau of Economic Research, Inc.
    3. David Rezza Baqaee & Emmanuel Farhi, 2018. "Macroeconomics with Heterogeneous Agents and Input-Output Networks," NBER Working Papers 24684, National Bureau of Economic Research, Inc.
    4. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "Economic Policy for Artificial Intelligence," Innovation Policy and the Economy, University of Chicago Press, vol. 19(1), pages 139-159.
    5. repec:gam:jscscx:v:8:y:2019:i:2:p:37-:d:201238 is not listed on IDEAS
    6. repec:gam:jsusta:v:10:y:2018:i:5:p:1661-:d:148182 is not listed on IDEAS
    7. repec:wfo:wstudy:61633 is not listed on IDEAS
    8. Ben Vermeulen & Jan Kesselhut & Andreas Pyka & Pier Paolo Saviotti, 2018. "The Impact of Automation on Employment: Just the Usual Structural Change?," Sustainability, MDPI, Open Access Journal, vol. 10(5), pages 1-27, May.
    9. Gilbert Cette & Lorraine Koehl & Thomas Philippon, 2019. "Labor Shares in Some Advanced Economies," NBER Working Papers 26136, National Bureau of Economic Research, Inc.
    10. Elena Crivellaro & Aikaterini Karadimitropoulou, 2019. "The role of financial constraints on labour share developments: macro- and micro-level evidence," Working Papers 257, Bank of Greece.
    11. Geiger, Niels & Prettner, Klaus & Schwarzer, Johannes A., 2018. "Automatisierung, Wachstum und Ungleichheit," Hohenheim Discussion Papers in Business, Economics and Social Sciences 13-2018, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    12. HAMAGUCHI Nobuaki & KONDO Keisuke, 2018. "Regional Employment and Artificial Intelligence in Japan," Discussion papers 18032, Research Institute of Economy, Trade and Industry (RIETI).
    13. Gregory Casey & Ryo Horii, 2019. "A Multi-factor Uzawa Growth Theorem and Endogenous Capital-Augmenting Technological Change," 2019 Meeting Papers 1458, Society for Economic Dynamics.
    14. Aquilante, Tommaso & Chowla, Shiv & Dacic, Nikola & Haldane, Andrew & Masolo, Riccardo & Schneider, Patrick & Seneca, Martin & Tatomir, Srdan, 2019. "Market power and monetary policy," Bank of England working papers 798, Bank of England.

    More about this item

    Keywords

    AI; automation; displacement effect; labor demand; inequality; productivity; tasks; technology; wages;

    JEL classification:

    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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