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The Allocation of Decision Authority to Human and Artificial Intelligence

Author

Listed:
  • Susan C. Athey
  • Kevin A. Bryan
  • Joshua S. Gans

Abstract

The allocation of decision authority by a principal to either a human agent or an artificial intelligence (AI) is examined. The principal trades off an AI’s more aligned choice with the need to motivate the human agent to expend effort in learning choice payoffs. When agent effort is desired, it is shown that the principal is more likely to give that agent decision authority, reduce investment in AI reliability and adopt an AI that may be biased. Organizational design considerations are likely to impact on how AI’s are trained.

Suggested Citation

  • Susan C. Athey & Kevin A. Bryan & Joshua S. Gans, 2020. "The Allocation of Decision Authority to Human and Artificial Intelligence," NBER Working Papers 26673, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:26673
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    References listed on IDEAS

    as
    1. 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.
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    3. 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, August.
    4. 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, August.
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    Cited by:

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    3. Christian Catalini & Xiang Hui & Jane Wu, 2026. "Some Simple Economics of AGI," Papers 2602.20946, arXiv.org, revised Feb 2026.
    4. Ari Hyytinen & Petri Rouvinen & Mika Pajarinen & Joosua Virtanen, 2023. "Ex Ante Predictability of Rapid Growth: A Design Science Approach," Entrepreneurship Theory and Practice, , vol. 47(6), pages 2465-2493, November.
    5. 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.
    6. Lyu, Wenjing & Liu, Jin, 2021. "Artificial Intelligence and emerging digital technologies in the energy sector," Applied Energy, Elsevier, vol. 303(C).
    7. Hyunjin Kim & Edward L. Glaeser & Andrew Hillis & Scott Duke Kominers & Michael Luca, 2024. "Decision authority and the returns to algorithms," Strategic Management Journal, Wiley Blackwell, vol. 45(4), pages 619-648, April.
    8. Bryce McLaughlin & Jann Spiess, 2022. "Algorithmic Assistance with Recommendation-Dependent Preferences," Papers 2208.07626, arXiv.org, revised Oct 2025.
    9. Laura Blattner & Scott Nelson & Jann Spiess, 2021. "Unpacking the Black Box: Regulating Algorithmic Decisions," Papers 2110.03443, arXiv.org, revised May 2024.
    10. Xienan Cheng & Mustafa Dogan & Pinar Yildirim, 2025. "Artificial Intelligence in Team Dynamics: Who Gets Replaced and Why?," Papers 2506.12337, arXiv.org, revised Mar 2026.
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    12. Maha Kalai & Hamdi Becha & Kamel Helali, 2024. "Effect of artificial intelligence on economic growth in European countries: a symmetric and asymmetric cointegration based on linear and non-linear ARDL approach," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 13(1), pages 1-37, December.
    13. Talia Gillis & Bryce McLaughlin & Jann Spiess, 2021. "On the Fairness of Machine-Assisted Human Decisions," Papers 2110.15310, arXiv.org, revised Sep 2023.
    14. Agrawal, Ajay & Gans, Joshua S. & Goldfarb, Avi, 2024. "Prediction machines, insurance, and protection: An alternative perspective on AI’s role in production," Journal of the Japanese and International Economies, Elsevier, vol. 72(C).
    15. Antonio Rodríguez Andrés & Voxi Heinrich S. Amavilah & Abraham Otero, 2021. "Evaluation of technology clubs by clustering: a cautionary note," Applied Economics, Taylor & Francis Journals, vol. 53(52), pages 5989-6001, November.
    16. Ashesh Rambachan & Jon Kleinberg & Sendhil Mullainathan & Jens Ludwig, 2020. "An Economic Approach to Regulating Algorithms," NBER Working Papers 27111, National Bureau of Economic Research, Inc.
    17. Caro-Burnett, Johann & Kaneko, Shinji, 2022. "Is Society Ready for AI Ethical Decision Making? Lessons from a Study on Autonomous Cars," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 98(C).
    18. Fabian Gaessler & Henning Piezunka, 2023. "Training with AI: Evidence from chess computers," Strategic Management Journal, Wiley Blackwell, vol. 44(11), pages 2724-2750, November.
    19. Jonathan Gruber & Benjamin R. Handel & Samuel H. Kina & Jonathan T. Kolstad, 2020. "Managing Intelligence: Skilled Experts and AI in Markets for Complex Products," NBER Working Papers 27038, National Bureau of Economic Research, Inc.
    20. Marie Obidzinski & Yves Oytana, 2022. "Advisory algorithms and liability rules," Working Papers hal-04222291, HAL.
    21. Feldhaus, Christoph & Lingens, Jörg & Löschel, Andreas & Zunker, Gerald, 2022. "Encouraging consumer activity through automatic switching of the electricity contract - A field experiment," Energy Policy, Elsevier, vol. 164(C).
    22. Mustafa Dogan & Alexandre Jacquillat & Pinar Yildirim, 2024. "Strategic automation and decision‐making authority," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(1), pages 203-246, January.
    23. Lambin, Xavier & Raizonville, Adrien, 2025. "From black box to glass box: algorithmic explainability as a strategic decision," Information Economics and Policy, Elsevier, vol. 71(C).
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    25. Bryce McLaughlin & Jann Spiess, 2024. "Designing Algorithmic Recommendations to Achieve Human-AI Complementarity," Papers 2405.01484, arXiv.org, revised Oct 2024.

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    JEL classification:

    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
    • M54 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Labor Management
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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