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How Artificial Intelligence and Machine Learning Can Impact Market Design

Author

Listed:
  • Paul R. Milgrom
  • Steven Tadelis

Abstract

In complex environments, it is challenging to learn enough about the underlying characteristics of transactions so as to design the best institutions to efficiently generate gains from trade. In recent years, Artificial Intelligence has emerged as an important tool that allows market designers to uncover important market fundamentals, and to better predict fluctuations that can cause friction in markets. This paper offers some recent examples of how Artificial Intelligence helps market designers improve the operations of markets, and outlines directions in which it will continue to shape and influence market design.

Suggested Citation

  • Paul R. Milgrom & Steven Tadelis, 2018. "How Artificial Intelligence and Machine Learning Can Impact Market Design," NBER Working Papers 24282, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:24282
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    Citations

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    Cited by:

    1. Eric J. Bartelsman, 2019. "From New Technology to Productivity," European Economy - Discussion Papers 113, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    2. David Bounies & Antoine Dubus & Patrick Waelbroeck, 2020. "Market for Information and Selling Mechanisms," Working Papers ECARES 2020-07, ULB -- Universite Libre de Bruxelles.
    3. David Bounie & Antoine Dubus & Patrick Waelbroeck, 2022. "Collecting and Selling Consumer Information: Selling Mechanisms Matter," Working Papers hal-02288708, HAL.
    4. Dangxing Chen & Luyao Zhang, 2023. "Monotonicity for AI ethics and society: An empirical study of the monotonic neural additive model in criminology, education, health care, and finance," Papers 2301.07060, arXiv.org.
    5. Lu Fang & Zhe Yuan & Kaifu Zhang & Dante Donati & Miklos Sarvary, 2025. "Generative AI and Firm Productivity: Field Experiments in Online Retail," Papers 2510.12049, arXiv.org, revised Feb 2026.
    6. Yan Chen & Peter Cramton & John A. List & Axel Ockenfels, 2021. "Market Design, Human Behavior, and Management," Management Science, INFORMS, vol. 67(9), pages 5317-5348, September.
    7. Yueqiang Xu & Petri Ahokangas & Jean-Nicolas Louis & Eva Pongrácz, 2019. "Electricity Market Empowered by Artificial Intelligence: A Platform Approach," Energies, MDPI, vol. 12(21), pages 1-21, October.
    8. Lu Fang & Zhe Yuan & Kaifu Zhang & Dante Donati & Miklos Sarvary, 2025. "Generative AI and Firm Productivity: Field Experiments in Online Retail," CESifo Working Paper Series 12201, CESifo.
    9. David Mayer-Foulkes, 2018. "Efficient Urbanization for Mexican Development," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(10), pages 1-1, October.
    10. Grazia Cecere & Thierry Pénard, 2020. "Introduction to the Special Issue: “From The digital economy to the digitalization of the economy”," Revue d'économie industrielle, De Boeck Université, vol. 0(4), pages 11-17.

    More about this item

    JEL classification:

    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality

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