IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/24839.html
   My bibliography  Save this paper

Artificial Intelligence, Economics, and Industrial Organization

Author

Listed:
  • Hal Varian

Abstract

Machine learning (ML) and artificial intelligence (AI) have been around for many years. However, in the last 5 years, remarkable progress has been made using multilayered neural networks in diverse areas such as image recognition, speech recognition, and machine translation. AI is a general purpose technology that is likely to impact many industries. In this chapter I consider how machine learning availability might affect the industrial organization of both firms that provide AI services and industries that adopt AI technology. My intent is not to provide an extensive overview of this rapidly-evolving area, but instead to provide a short summary of some of the forces at work and to describe some possible areas for future research.

Suggested Citation

  • Hal Varian, 2018. "Artificial Intelligence, Economics, and Industrial Organization," NBER Working Papers 24839, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:24839
    Note: IO PR
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w24839.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ilya Segal, 2003. "Optimal Pricing Mechanisms with Unknown Demand," American Economic Review, American Economic Association, vol. 93(3), pages 509-529, June.
    2. Alessandro Acquisti & Hal R. Varian, 2005. "Conditioning Prices on Purchase History," Marketing Science, INFORMS, vol. 24(3), pages 367-381, May.
    3. Varian, Hal R., 1989. "Price discrimination," Handbook of Industrial Organization, in: R. Schmalensee & R. Willig (ed.), Handbook of Industrial Organization, edition 1, volume 1, chapter 10, pages 597-654, Elsevier.
    4. Alessandro Acquisti & Curtis Taylor & Liad Wagman, 2016. "The Economics of Privacy," Journal of Economic Literature, American Economic Association, vol. 54(2), pages 442-492, June.
    5. K. J. Arrow, 1971. "The Economic Implications of Learning by Doing," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 11, pages 131-149, Palgrave Macmillan.
    6. Igal Hendel & Yossi Spiegel, 2014. "Small Steps for Workers, a Giant Leap for Productivity," American Economic Journal: Applied Economics, American Economic Association, vol. 6(1), pages 73-90, January.
    7. Rubinstein, Ariel, 1986. "Finite automata play the repeated prisoner's dilemma," Journal of Economic Theory, Elsevier, vol. 39(1), pages 83-96, June.
    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. Muzaffer Buyruk & Ertan Güner, 2022. "Personalization in airline revenue management: an overview and future outlook," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(2), pages 129-139, April.
    2. Dengler, Sebastian & Prüfer, Jens, 2021. "Consumers' privacy choices in the era of big data," Games and Economic Behavior, Elsevier, vol. 130(C), pages 499-520.
    3. Stole, Lars A., 2007. "Price Discrimination and Competition," Handbook of Industrial Organization, in: Mark Armstrong & Robert Porter (ed.), Handbook of Industrial Organization, edition 1, volume 3, chapter 34, pages 2221-2299, Elsevier.
    4. Long Chen & Yadong Huang & Shumiao Ouyang & Wei Xiong, 2021. "The Data Privacy Paradox and Digital Demand," Working Papers 2021-47, Princeton University. Economics Department..
    5. Daron Acemoglu & Ali Makhdoumi & Azarakhsh Malekian & Asu Ozdaglar, 2022. "Too Much Data: Prices and Inefficiencies in Data Markets," American Economic Journal: Microeconomics, American Economic Association, vol. 14(4), pages 218-256, November.
    6. Oliver Budzinski & Annika Stöhr, 2019. "Competition policy reform in Europe and Germany – institutional change in the light of digitization," European Competition Journal, Taylor & Francis Journals, vol. 15(1), pages 15-54, January.
    7. Catherine Tucker, 2023. "The Economics of Privacy: An Agenda," NBER Chapters, in: The Economics of Privacy, National Bureau of Economic Research, Inc.
    8. Lagerlöf, Johan N.M., 2023. "Surfing incognito: Welfare effects of anonymous shopping," International Journal of Industrial Organization, Elsevier, vol. 87(C).
    9. Didier Laussel & Ngo Van Long & Joana Resende, 2023. "Profit Effects of Consumers’ Identity Management: A Dynamic Model," Management Science, INFORMS, vol. 69(6), pages 3602-3615, June.
    10. Yash Kanoria & Hamid Nazerzadeh, 2020. "Dynamic Reserve Prices for Repeated Auctions: Learning from Bids," Papers 2002.07331, arXiv.org.
    11. Clavorà Braulin, Francesco, 2021. "The effects of personal information on competition: Consumer privacy and partial price discrimination," ZEW Discussion Papers 21-007, ZEW - Leibniz Centre for European Economic Research.
    12. Li, Jianpei & Zhang, Wanzhu, 2022. "Behavior-based pricing and signaling of product quality," MPRA Paper 120263, University Library of Munich, Germany, revised 03 Jan 2023.
    13. Budzinski, Oliver, 2016. "Aktuelle Herausforderungen der Wettbewerbspolitik durch Marktplätze im Internet," Ilmenau Economics Discussion Papers 103, Ilmenau University of Technology, Institute of Economics.
    14. Chiara Conti & Pierfrancesco Reverberi, 2019. "Price discrimination and product quality under opt-in privacy regulation," DIAG Technical Reports 2019-07, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    15. Skreta, Vasiliki & Doval, Laura, 2021. "Purchase history and product personalization," CEPR Discussion Papers 15969, C.E.P.R. Discussion Papers.
    16. Budzinski, Oliver & Gänßle, Sophia & Lindstädt-Dreusicke, Nadine, 2021. "Data (r)evolution - The economics of algorithmic search and recommender services," Ilmenau Economics Discussion Papers 148, Ilmenau University of Technology, Institute of Economics.
    17. Kobbi Nissim & Rann Smorodinsky & Moshe Tennenholtz, 2018. "Segmentation, Incentives, and Privacy," Mathematics of Operations Research, INFORMS, vol. 43(4), pages 1252-1268, November.
    18. Li, Jianpei & Zhang, Wanzhu, 2024. "The Value of Anonymous Option," MPRA Paper 120010, University Library of Munich, Germany.
    19. Rodrigo Montes & Wilfried Sand-Zantman & Tommaso Valletti, 2019. "The Value of Personal Information in Online Markets with Endogenous Privacy," Management Science, INFORMS, vol. 65(3), pages 1342-1362, March.
    20. Budzinski, Oliver & Schneider, Sonja, 2017. "Smart Fitness: Ökonomische Effekte einer Digitalisierung der Selbstvermessung," Ilmenau Economics Discussion Papers 105, Ilmenau University of Technology, Institute of Economics.

    More about this item

    JEL classification:

    • L0 - Industrial Organization - - General

    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:24839. 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.