IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/30177.html
   My bibliography  Save this paper

Prediction Machines, Insurance, and Protection: An Alternative Perspective on AI's Role in Production

Author

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

Abstract

Recent advances in AI represent improvements in prediction. We examine how decision-making and risk management strategies change when prediction improves. The adoption of AI may cause substitution away from risk management activities used when rules are applied (rules require always taking the same action), instead allowing for decision-making (choosing actions based on the predicted state). We provide a formal model evaluating the impact of AI and how risk management, stakes, and inter-related tasks affect AI adoption. The broad conclusion is that AI adoption can be stymied by existing processes designed to address uncertainty. In particular, many processes are designed to enable coordinated decision-making among different actors in an organization. AI can make coordination even more challenging. However, when the cost of changing such processes falls, then the returns from AI adoption increase.

Suggested Citation

  • Ajay K. Agrawal & Joshua S. Gans & Avi Goldfarb, 2022. "Prediction Machines, Insurance, and Protection: An Alternative Perspective on AI's Role in Production," NBER Working Papers 30177, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:30177
    Note: PR
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w30177.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    2. Agrawal, Ajay & Gans, Joshua S. & Goldfarb, Avi, 2019. "Exploring the impact of artificial Intelligence: Prediction versus judgment," Information Economics and Policy, Elsevier, vol. 47(C), pages 1-6.
    3. David J. Deming, 2021. "The Growing Importance of Decision-Making on the Job," NBER Working Papers 28733, National Bureau of Economic Research, Inc.
    4. Susan C. Athey & Kevin A. Bryan & Joshua S. Gans, 2020. "The Allocation of Decision Authority to Human and Artificial Intelligence," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 80-84, May.
    5. repec:bla:scandj:v:90:y:1988:i:3:p:275-89 is not listed on IDEAS
    6. Joshua S. Gans, 2023. "Artificial intelligence adoption in a monopoly market," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(2), pages 1098-1106, March.
    7. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2018. "Prediction, Judgment, and Complexity: A Theory of Decision-Making and Artificial Intelligence," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 89-110, National Bureau of Economic Research, Inc.
    8. Morgan R. Frank & David Autor & James E. Bessen & Erik Brynjolfsson & Manuel Cebrian & David J. Deming & Maryann Feldman & Matthew Groh & José Lobo & Esteban Moro & Dashun Wang & Hyejin Youn & Iyad Ra, 2019. "Toward understanding the impact of artificial intelligence on labor," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 116(14), pages 6531-6539, April.
    9. Ehrlich, Isaac & Becker, Gary S, 1972. "Market Insurance, Self-Insurance, and Self-Protection," Journal of Political Economy, University of Chicago Press, vol. 80(4), pages 623-648, July-Aug..
    10. Edward W. Felten & Manav Raj & Robert Seamans, 2018. "A Method to Link Advances in Artificial Intelligence to Occupational Abilities," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 54-57, May.
    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. Fossen, Frank M. & Sorgner, Alina, 2022. "New digital technologies and heterogeneous wage and employment dynamics in the United States: Evidence from individual-level data," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    2. Montobbio, Fabio & Staccioli, Jacopo & Virgillito, Maria Enrica & Vivarelli, Marco, 2022. "Robots and the origin of their labour-saving impact," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    3. Ozgun, Burcu & Broekel, Tom, 2021. "The geography of innovation and technology news - An empirical study of the German news media," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    4. Dosi, G. & Piva, M. & Virgillito, M.E. & Vivarelli, M., 2021. "Embodied and disembodied technological change: The sectoral patterns of job-creation and job-destruction," Research Policy, Elsevier, vol. 50(4).
    5. Ekaterina Prytkova & Fabien Petit & Deyu Li & Sugat Chaturvedi & Tommaso Ciarli, 2024. "The Employment Impact of Emerging Digital Technologies," CEPEO Working Paper Series 24-01, UCL Centre for Education Policy and Equalising Opportunities, revised Feb 2024.
    6. Joshua S. Gans, 2023. "Artificial intelligence adoption in a competitive market," Economica, London School of Economics and Political Science, vol. 90(358), pages 690-705, April.
    7. Roberto Antonietti & Luca Cattani & Francesca Gambarotto & Giulio Pedrini, 2021. "Education, routine, and complexity-biased Knowledge Enabling Technologies: Evidence from Emilia-Romagna, Italy," Discussion Paper series in Regional Science & Economic Geography 2021-07, Gran Sasso Science Institute, Social Sciences, revised May 2021.
    8. Bauer, Kevin & von Zahn, Moritz & Hinz, Oliver, 2023. "Please take over: XAI, delegation of authority, and domain knowledge," SAFE Working Paper Series 394, Leibniz Institute for Financial Research SAFE.
    9. Genz, Sabrina & Schnabel, Claus, 2021. "Digging into the Digital Divide: Workers' Exposure to Digitalization and Its Consequences for Individual Employment," IZA Discussion Papers 14649, Institute of Labor Economics (IZA).
    10. Erdem Dogukan Yilmaz & Christian Peukert, 2024. "Who Benefits from AI? Project-Level Evidence on Labor Demand, Operations and Profitability," CESifo Working Paper Series 11321, CESifo.
    11. Zou, Jing & Deng, Xiaojun, 2022. "Housing tenure choice and socio-economic integration of migrants in rising cities of China," China Economic Review, Elsevier, vol. 74(C).
    12. Caselli, Mauro & Fracasso, Andrea & Scicchitano, Sergio & Traverso, Silvio & Tundis, Enrico, 2021. "Stop worrying and love the robot: An activity-based approach to assess the impact of robotization on employment dynamics," GLO Discussion Paper Series 802, Global Labor Organization (GLO).
    13. Benjamin Meindl & Morgan R. Frank & Joana Mendonc{c}a, 2021. "Exposure of occupations to technologies of the fourth industrial revolution," Papers 2110.13317, arXiv.org.
    14. Ed Felten & Manav Raj & Robert Seamans, 2023. "How will Language Modelers like ChatGPT Affect Occupations and Industries?," Papers 2303.01157, arXiv.org, revised Mar 2023.
    15. Montobbio, Fabio & Staccioli, Jacopo & Virgillito, Maria Enrica & Vivarelli, Marco, 2021. "Labour-saving automation and occupational exposure: a text-similarity measure," GLO Discussion Paper Series 987, Global Labor Organization (GLO).
    16. Jean-Philippe Deranty & Thomas Corbin, 2022. "Artificial Intelligence and work: a critical review of recent research from the social sciences," Papers 2204.00419, arXiv.org.
    17. Qin Chen & Jinfeng Ge & Huaqing Xie & Xingcheng Xu & Yanqing Yang, 2023. "Large Language Models at Work in China's Labor Market," Papers 2308.08776, arXiv.org.
    18. 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.
    19. Wang, Heting & Wang, Huijuan & Guan, Rong, 2024. "Digitalization of industries and labor mobility in China," China Economic Review, Elsevier, vol. 87(C).
    20. Fossen, Frank M. & McLemore, Trevor & Sorgner, Alina, 2024. "Artificial Intelligence and Entrepreneurship," IZA Discussion Papers 17055, Institute of Labor Economics (IZA).

    More about this item

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:nbr:nberwo:30177. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.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.