IDEAS home Printed from https://ideas.repec.org/a/eee/gamebe/v153y2025icp254-267.html

Working with AI: An analysis for rational integration

Author

Listed:
  • Lagziel, David
  • Tsodikovich, Yevgeny

Abstract

A decision maker (DM) uses an AI agent to estimate an unknown state, for which both possess informative private signals. Conditional on the state and the DM's final assessment, he prefers the AI's recommendations to be incorrect, thus affirming his own superiority or sharing the blame. Our analysis indicates that the correctness of the process is not a monotone function of participants' expertise levels: (i) a less accurate AI may lead to improved outcomes by reducing the DM's reliance on it, and (ii) a less accurate DM can enhance information aggregation leading to a superior result.

Suggested Citation

  • Lagziel, David & Tsodikovich, Yevgeny, 2025. "Working with AI: An analysis for rational integration," Games and Economic Behavior, Elsevier, vol. 153(C), pages 254-267.
    • Handle: RePEc:eee:gamebe:v:153:y:2025:i:c:p:254-267
    DOI: 10.1016/j.geb.2025.06.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0899825625000934
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.geb.2025.06.009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Kyogo Kanazawa & Daiji Kawaguchi & Hitoshi Shigeoka & Yasutora Watanabe, 2026. "AI, Skill, and Productivity: The Case of Taxi Drivers," Management Science, INFORMS, vol. 72(2), pages 1376-1388, February.
    2. Victoria Angelova & Will S. Dobbie & Crystal Yang, 2023. "Algorithmic Recommendations and Human Discretion," NBER Working Papers 31747, National Bureau of Economic Research, Inc.
    3. David Lagziel & Ehud Lehrer, 2019. "A Bias of Screening," American Economic Review: Insights, American Economic Association, vol. 1(3), pages 343-356, December.
    4. Senthil K. Veeraraghavan & Laurens G. Debo, 2011. "Herding in Queues with Waiting Costs: Rationality and Regret," Manufacturing & Service Operations Management, INFORMS, vol. 13(3), pages 329-346, July.
    5. Lones Smith & Peter Sorensen, 2000. "Pathological Outcomes of Observational Learning," Econometrica, Econometric Society, vol. 68(2), pages 371-398, March.
    6. Jens Ludwig & Sendhil Mullainathan, 2021. "Fragile Algorithms and Fallible Decision-Makers: Lessons from the Justice System," Journal of Economic Perspectives, American Economic Association, vol. 35(4), pages 71-96, Fall.
    7. S. Ali & Navin Kartik, 2012. "Herding with collective preferences," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 51(3), pages 601-626, November.
    8. Sushil Bikhchandani & David Hirshleifer & Omer Tamuz & Ivo Welch, 2024. "Information Cascades and Social Learning," Journal of Economic Literature, American Economic Association, vol. 62(3), pages 1040-1093, September.
    9. David Lagziel & Ehud Lehrer, 2022. "Screening Dominance: A Comparison of Noisy Signals," American Economic Journal: Microeconomics, American Economic Association, vol. 14(4), pages 1-24, November.
    10. Sendhil Mullainathan & Ziad Obermeyer, 2022. "Diagnosing Physician Error: A Machine Learning Approach to Low-Value Health Care [“The Determinants of Productivity in Medical Testing: Intensity and Allocation of Care,”]," The Quarterly Journal of Economics, Oxford University Press, vol. 137(2), pages 679-727.
    11. Nikhil Agarwal & Alex Moehring & Pranav Rajpurkar & Tobias Salz, 2023. "Combining Human Expertise with Artificial Intelligence: Experimental Evidence from Radiology," NBER Working Papers 31422, National Bureau of Economic Research, Inc.
    12. Lones Smith & Peter Norman Sørensen & Jianrong Tian, 2021. "Informational Herding, Optimal Experimentation, and Contrarianism [The Market for “Lemons”: Quality Uncertainty and the Market Mechanism]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(5), pages 2527-2554.
    13. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    14. Ashesh Rambachan, 2024. "Identifying Prediction Mistakes in Observational Data," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 139(3), pages 1665-1711.
    15. Scharfstein, David S & Stein, Jeremy C, 1990. "Herd Behavior and Investment," American Economic Review, American Economic Association, vol. 80(3), pages 465-479, June.
    16. Michelle Vaccaro & Abdullah Almaatouq & Thomas Malone, 2024. "When combinations of humans and AI are useful: A systematic review and meta-analysis," Nature Human Behaviour, Nature, vol. 8(12), pages 2293-2303, December.
    17. 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.
    18. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    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. David Lagziel & Yevgeny Tsodikovich, 2023. "Second Opinions and the Humility Threshold," Working Papers 2305, Ben-Gurion University of the Negev, Department of Economics.
    2. Eyster, Erik & Galeotti, Andrea & Kartik, Navin & Rabin, Matthew, 2014. "Congested observational learning," Games and Economic Behavior, Elsevier, vol. 87(C), pages 519-538.
    3. Hirshleifer, David & Teoh, Siew Hong, 2008. "Thought and Behavior Contagion in Capital Markets," MPRA Paper 9164, University Library of Munich, Germany.
    4. Runshan Fu & Ginger Zhe Jin & Meng Liu, 2022. "Does Human-algorithm Feedback Loop Lead to Error Propagation? Evidence from Zillow’s Zestimate," NBER Working Papers 29880, National Bureau of Economic Research, Inc.
    5. Puput Tri Komalasari & Marwan Asri & Bernardinus M. Purwanto & Bowo Setiyono, 2022. "Herding behaviour in the capital market: What do we know and what is next?," Management Review Quarterly, Springer, vol. 72(3), pages 745-787, September.
    6. Stone, Daniel F. & Miller, Steven J., 2013. "Leading, learning and herding," Mathematical Social Sciences, Elsevier, vol. 65(3), pages 222-231.
    7. repec:esx:essedp:706 is not listed on IDEAS
    8. Dasgupta, Amil & Prat, Andrea, 2008. "Information aggregation in financial markets with career concerns," Journal of Economic Theory, Elsevier, vol. 143(1), pages 83-113, November.
    9. Fernández-Duque, Mauricio, 2022. "The probability of pluralistic ignorance," Journal of Economic Theory, Elsevier, vol. 202(C).
    10. Paolo Balduzzi, 2005. "Optimal use of scarce information: When partisan voters are socially useful," Working Papers 87, University of Milano-Bicocca, Department of Economics, revised Mar 2005.
    11. Drehmann, Mathias & Oechssler, Jorg & Roider, Andreas, 2007. "Herding with and without payoff externalities -- an internet experiment," International Journal of Industrial Organization, Elsevier, vol. 25(2), pages 391-415, April.
    12. Toxopeus, Helen & Polzin, Friedemann & Cai, Wanxiang & Huisman, Ronald, 2025. "Investor types and campaign dynamics in investment crowdfunding: A herding and collective action perspective," Research Policy, Elsevier, vol. 54(9).
    13. Li Chen & Yiangos Papanastasiou, 2021. "Seeding the Herd: Pricing and Welfare Effects of Social Learning Manipulation," Management Science, INFORMS, vol. 67(11), pages 6734-6750, November.
    14. Arieli, Itai, 2017. "Payoff externalities and social learning," Games and Economic Behavior, Elsevier, vol. 104(C), pages 392-410.
    15. Smirnov, Aleksei & Starkov, Egor, 2025. "Designing social learning," European Economic Review, Elsevier, vol. 178(C).
    16. Xu, Wenji, 2025. "Social learning through coarse signals of others' actions," Journal of Economic Theory, Elsevier, vol. 229(C).
    17. Keppo, Jussi & Satopää, Ville A., 2024. "Bayesian herd detection for dynamic data," International Journal of Forecasting, Elsevier, vol. 40(1), pages 285-301.
    18. Florian Brandl, 2025. "The Social Learning Barrier," Papers 2504.12136, arXiv.org, revised Aug 2025.
    19. Peter Sorensen & Marco Ottaviani, 2000. "Herd Behavior and Investment: Comment," American Economic Review, American Economic Association, vol. 90(3), pages 695-704, June.
    20. Elchanan Mossel & Manuel Mueller‐Frank & Allan Sly & Omer Tamuz, 2020. "Social Learning Equilibria," Econometrica, Econometric Society, vol. 88(3), pages 1235-1267, May.
    21. Song, Yangbo, 2025. "Social learning among opinion leaders," Games and Economic Behavior, Elsevier, vol. 153(C), pages 451-473.

    More about this item

    Keywords

    ;
    ;
    ;

    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:eee:gamebe:v:153:y:2025:i:c:p:254-267. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/622836 .

    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.