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The Allocation of Decision Authority to Human and Artificial Intelligence

Author

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  • 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 have an impact on how AIs are trained.

Suggested Citation

  • 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.
    • Handle: RePEc:aea:apandp:v:110:y:2020:p:80-84
    DOI: 10.1257/pandp.20201034
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    References listed on IDEAS

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    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, October.
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    Cited by:

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    2. 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.
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    6. Bryce McLaughlin & Jann Spiess, 2022. "Algorithmic Assistance with Recommendation-Dependent Preferences," Papers 2208.07626, arXiv.org, revised Jan 2024.
    7. 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).
    8. 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.
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    11. 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.
    12. 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.
    13. Laura Abrardi & Carlo Cambini & Laura Rondi, 2022. "Artificial intelligence, firms and consumer behavior: A survey," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 969-991, September.
    14. 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.
    15. Lyu, Wenjing & Liu, Jin, 2021. "Artificial Intelligence and emerging digital technologies in the energy sector," Applied Energy, Elsevier, vol. 303(C).
    16. 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).
    17. Marie Obidzinski & Yves Oytana, 2022. "Prediction, human decision and liability rules, CRED Working paper No 2022-06," Working Papers hal-04034871, HAL.
    18. Laura Blattner & Scott Nelson & Jann Spiess, 2021. "Unpacking the Black Box: Regulating Algorithmic Decisions," Papers 2110.03443, arXiv.org, revised May 2024.
    19. 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).
    20. Bryce McLaughlin & Jann Spiess, 2024. "Designing Algorithmic Recommendations to Achieve Human-AI Complementarity," Papers 2405.01484, arXiv.org, revised Oct 2024.
    21. Talia Gillis & Bryce McLaughlin & Jann Spiess, 2021. "On the Fairness of Machine-Assisted Human Decisions," Papers 2110.15310, arXiv.org, revised Sep 2023.

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    More about this item

    JEL classification:

    • D23 - Microeconomics - - Production and Organizations - - - Organizational Behavior; Transaction Costs; Property Rights
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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