IDEAS home Printed from https://ideas.repec.org/a/aea/jecper/v33y2019i2p31-50.html
   My bibliography  Save this article

Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction

Author

Listed:
  • Ajay Agrawal
  • Joshua S. Gans
  • Avi Goldfarb

Abstract

Recent advances in artificial intelligence are primarily driven by machine learning, a prediction technology. Prediction is useful because it is an input into decision-making. In order to appreciate the impact of artificial intelligence on jobs, it is important to understand the relative roles of prediction and decision tasks. We describe and provide examples of how artificial intelligence will affect labor, emphasizing differences between when the automation of prediction leads to automating decisions versus enhancing decision-making by humans.

Suggested Citation

  • Ajay Agrawal & Joshua S. Gans & Avi Goldfarb, 2019. "Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 31-50, Spring.
    • Handle: RePEc:aea:jecper:v:33:y:2019:i:2:p:31-50
    Note: DOI: 10.1257/jep.33.2.31
    as

    Download full text from publisher

    File URL: https://www.aeaweb.org/doi/10.1257/jep.33.2.31
    Download Restriction: no
    File URL: https://www.aeaweb.org/articles/attachments?retrieve=hoIc6NFPSoSXSPX6b9d7yp89lN6buZo1
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Bresnahan, Timothy F. & Trajtenberg, M., 1995. "General purpose technologies 'Engines of growth'?," Journal of Econometrics, Elsevier, vol. 65(1), pages 83-108, January.
    2. Anders Akerman & Ingvil Gaarder & Magne Mogstad, 2015. "The Skill Complementarity of Broadband Internet," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(4), pages 1781-1824.
    3. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
    4. Acemoglu, Daron & Autor, David, 2011. "Skills, Tasks and Technologies: Implications for Employment and Earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 12, pages 1043-1171, Elsevier.
    5. O. Ashenfelter & D. Card (ed.), 2011. "Handbook of Labor Economics," Handbook of Labor Economics, Elsevier, edition 1, volume 4, number 5.
    6. Pascual Restrepo, 2019. "Automation and New Tasks: The Implications of the Task Content of Production for Labor Demand," 2019 Meeting Papers 234, Society for Economic Dynamics.
    7. Erik Brynjolfsson & Xiang Hui & Meng Liu, 2019. "Does Machine Translation Affect International Trade? Evidence from a Large Digital Platform," Management Science, INFORMS, vol. 65(12), pages 5449-5460, December.
    8. David Autor & Anna Salomons, 2018. "Is Automation Labor-Displacing? Productivity Growth, Employment, and the Labor Share," NBER Working Papers 24871, National Bureau of Economic Research, Inc.
    9. Susan Athey & Guido W. Imbens, 2017. "The State of Applied Econometrics: Causality and Policy Evaluation," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 3-32, Spring.
    10. 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.
    11. Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
    12. repec:bin:bpeajo:v:49:y:2019:i:2018-01:p:1-87 is not listed on IDEAS
    13. Sendhil Mullainathan & Jann Spiess, 2017. "Machine Learning: An Applied Econometric Approach," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 87-106, Spring.
    14. Jon Kleinberg & Himabindu Lakkaraju & Jure Leskovec & Jens Ludwig & Sendhil Mullainathan, 2018. "Human Decisions and Machine Predictions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(1), pages 237-293.
    15. Agrawal, Ajay & Gans, Joshua & Goldfarb, Avi (ed.), 2019. "The Economics of Artificial Intelligence," National Bureau of Economic Research Books, University of Chicago Press, number 9780226613338.
    16. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "The Economics of Artificial Intelligence: An Agenda," NBER Books, National Bureau of Economic Research, Inc, number agra-1, June.
    17. 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.
    18. O. Ashenfelter & D. Card (ed.), 2011. "Handbook of Labor Economics," Handbook of Labor Economics, Elsevier, edition 1, volume 4, number 4.
    Full references (including those not matched with items on IDEAS)

    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. Matthias Firgo & Peter Mayerhofer & Michael Peneder & Philipp Piribauer & Peter Reschenhofer, 2018. "Beschäftigungseffekte der Digitalisierung in den Bundesländern sowie in Stadt und Land," WIFO Studies, WIFO, number 61633.
    2. Anderton, Robert & Jarvis, Valerie & Labhard, Vincent & Morgan, Julian & Petroulakis, Filippos & Vivian, Lara, 2020. "Virtually everywhere? Digitalisation and the euro area and EU economies," Occasional Paper Series 244, European Central Bank.
    3. Barbieri, Laura & Mussida, Chiara & Piva, Mariacristina & Vivarelli, Marco, 2019. "Testing the Employment Impact of Automation, Robots and AI: A Survey and Some Methodological Issues," IZA Discussion Papers 12612, Institute of Labor Economics (IZA).
    4. Gries, Thomas & Naudé, Wim, 2022. "Modelling artificial intelligence in economics," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 56, pages 1-12.
    5. Sergio De Nardis & Francesca Parente, 2022. "Technology and task changes in the major EU countries," Contemporary Economic Policy, Western Economic Association International, vol. 40(2), pages 391-413, April.
    6. Fossen, Frank M. & Sorgner, Alina, 2019. "New Digital Technologies and Heterogeneous Employment and Wage Dynamics in the United States: Evidence from Individual-Level Data," IZA Discussion Papers 12242, Institute of Labor Economics (IZA).
    7. Van Roy, Vincent & Vertesy, Daniel & Damioli, Giacomo, 2019. "AI and Robotics Innovation: a Sectoral and Geographical Mapping using Patent Data," GLO Discussion Paper Series 433, Global Labor Organization (GLO).
    8. Barbieri, Laura & Mussida, Chiara & Piva, Mariacristina & Vivarelli, Marco, 2019. "Testing the employment and skill impact of new technologies: A survey and some methodological issues," MERIT Working Papers 2019-032, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    9. Cirillo, Valeria & Evangelista, Rinaldo & Guarascio, Dario & Sostero, Matteo, 2021. "Digitalization, routineness and employment: An exploration on Italian task-based data," Research Policy, Elsevier, vol. 50(7).
    10. Björn Döhring & Atanas Hristov & Christoph Maier & Werner Roeger & Anna Thum-Thysen, 2021. "COVID-19 acceleration in digitalisation, aggregate productivity growth and the functional income distribution," International Economics and Economic Policy, Springer, vol. 18(3), pages 571-604, July.
    11. Andres, Antonio Rodriguez & Otero, Abraham & Amavilah, Voxi Heinrich, 2021. "Using Deep Learning Neural Networks to Predict the Knowledge Economy Index for Developing and Emerging Economies," MPRA Paper 109137, University Library of Munich, Germany.
    12. Tatiana de Macedo Nogueira Lima, 2022. "Documento de Trabalho 03/2022 - Aprendizado de máquina e antitruste," Documentos de Trabalho 2022030, Conselho Administrativo de Defesa Econômica (Cade), Departamento de Estudos Econômicos.
    13. Arntz, Melanie & Gregory, Terry & Zierahn, Ulrich, 2019. "Digitalization and the future of work: Macroeconomic consequences," ZEW Discussion Papers 19-024, ZEW - Leibniz Centre for European Economic Research.
    14. Nicholas Bloom & Tarek Alexander Hassan & Aakash Kalyani & Josh Lerner & Ahmed Tahoun, 2021. "The diffusion of disruptive technologies," CEP Discussion Papers dp1798, Centre for Economic Performance, LSE.
    15. Byron Botha & Rulof Burger & Kevin Kotzé & Neil Rankin & Daan Steenkamp, 2023. "Big data forecasting of South African inflation," Empirical Economics, Springer, vol. 65(1), pages 149-188, July.
    16. Laura Abrardi & Carlo Cambini & Laura Rondi, 2022. "Artificial intelligence, firms and consumer behavior: A survey," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 969-991, September.
    17. Daisuke Miyakawa & Kohei Shintani, 2020. "Disagreement between Human and Machine Predictions," IMES Discussion Paper Series 20-E-11, Institute for Monetary and Economic Studies, Bank of Japan.
    18. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    19. Georg Graetz & Guy Michaels, 2018. "Robots at Work," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 753-768, December.
    20. Monica Andini & Emanuele Ciani & Guido de Blasio & Alessio D'Ignazio & Viola Salvestrini, 2017. "Targeting policy-compliers with machine learning: an application to a tax rebate programme in Italy," Temi di discussione (Economic working papers) 1158, Bank of Italy, Economic Research and International Relations Area.

    More about this item

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • 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
    • L23 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Organization of Production
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management

    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:aea:jecper:v:33:y:2019:i:2:p:31-50. 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: Michael P. Albert (email available below). General contact details of provider: https://edirc.repec.org/data/aeaaaea.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.