IDEAS home Printed from https://ideas.repec.org/a/zbw/espost/249297.html
   My bibliography  Save this article

People prefer moral discretion to algorithms: Algorithm aversion beyond intransparency

Author

Listed:
  • Jauernig, Johanna
  • Uhl, Matthias
  • Walkowitz, Gari

Abstract

We explore aversion to the use of algorithms in moral decision-making. So far, this aversion has been explained mainly by the fear of opaque decisions that are potentially biased. Using incentivized experiments, we study which role the desire for human discretion in moral decision-making plays. This seems justified in light of evidence suggesting that people might not doubt the quality of algorithmic decisions, but still reject them. In our first study, we found that people prefer humans with decision-making discretion to algorithms that rigidly apply exogenously given human-created fairness principles to specific cases. In the second study, we found that people do not prefer humans to algorithms because they appreciate flesh-and-blood decision-makers per se, but because they appreciate humans' freedom to transcend fairness principles at will. Our results contribute to a deeper understanding of algorithm aversion. They indicate that emphasizing the transparency of algorithms that clearly follow fairness principles might not be the only element for fostering societal algorithm acceptance and suggest reconsidering certain features of the decision-making process.

Suggested Citation

  • Jauernig, Johanna & Uhl, Matthias & Walkowitz, Gari, 2022. "People prefer moral discretion to algorithms: Algorithm aversion beyond intransparency," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 35(1).
  • Handle: RePEc:zbw:espost:249297
    DOI: 10.1007/s13347-021-00495-y
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/249297/1/Jauernig_2022_moral_discretion.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.1007/s13347-021-00495-y?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
    ---><---

    References listed on IDEAS

    as
    1. Chiara Longoni & Andrea Bonezzi & Carey K Morewedge, 2019. "Resistance to Medical Artificial Intelligence," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 46(4), pages 629-650.
    2. Ben Greiner, 2015. "Subject pool recruitment procedures: organizing experiments with ORSEE," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 1(1), pages 114-125, July.
    3. Kim, Tae Wan & Monge, Rosemarie & Strudler, Alan, 2015. "Bounded Ethicality and The Principle That “Ought†Implies “Canâ€," Business Ethics Quarterly, Cambridge University Press, vol. 25(3), pages 341-361, July.
    4. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    5. Juan D. Carrillo & Thomas Mariotti, 2000. "Strategic Ignorance as a Self-Disciplining Device," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 67(3), pages 529-544.
    6. Furnham, Adrian & Boo, Hua Chu, 2011. "A literature review of the anchoring effect," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 40(1), pages 35-42, February.
    7. David Gill & Victoria Prowse, 2012. "A Structural Analysis of Disappointment Aversion in a Real Effort Competition," American Economic Review, American Economic Association, vol. 102(1), pages 469-503, February.
    8. Bettman, James R. & Johnson, Eric J. & Payne, John W., 1990. "A componential analysis of cognitive effort in choice," Organizational Behavior and Human Decision Processes, Elsevier, vol. 45(1), pages 111-139, February.
    9. Linda Babcock & George Loewenstein, 1997. "Explaining Bargaining Impasse: The Role of Self-Serving Biases," Journal of Economic Perspectives, American Economic Association, vol. 11(1), pages 109-126, Winter.
    10. Zachary Grossman & Joël J. van der Weele, 2017. "Self-Image and Willful Ignorance in Social Decisions," Journal of the European Economic Association, European Economic Association, vol. 15(1), pages 173-217.
    11. Thomas R. Insel, 2019. "How algorithms could bring empathy back to medicine," Nature, Nature, vol. 567(7747), pages 172-173, March.
    12. Gogoll, Jan & Uhl, Matthias, 2018. "Rage against the machine: Automation in the moral domain," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 74(C), pages 97-103.
    13. David Eil & Justin M. Rao, 2011. "The Good News-Bad News Effect: Asymmetric Processing of Objective Information about Yourself," American Economic Journal: Microeconomics, American Economic Association, vol. 3(2), pages 114-138, May.
    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. Lisa Bruttel & Werner Güth & Ralph Hertwig & Andreas Orland, 2020. "Do people harness deliberate ignorance to avoid envy and its detrimental effects?," CEPA Discussion Papers 17, Center for Economic Policy Analysis.
    2. Ging-Jehli, Nadja R. & Schneider, Florian H. & Weber, Roberto A., 2020. "On self-serving strategic beliefs," Games and Economic Behavior, Elsevier, vol. 122(C), pages 341-353.
    3. Kai Barron & Christina Gravert, 2022. "Confidence and Career Choices: An Experiment," Scandinavian Journal of Economics, Wiley Blackwell, vol. 124(1), pages 35-68, January.
    4. Guy Mayraz, 2011. "Wishful Thinking," CEP Discussion Papers dp1092, Centre for Economic Performance, LSE.
    5. Murad, Zahra & Starmer, Chris, 2021. "Confidence snowballing and relative performance feedback," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 550-572.
    6. Simon Gächter & Lingbo Huang & Martin Sefton, 2016. "Combining “real effort” with induced effort costs: the ball-catching task," Experimental Economics, Springer;Economic Science Association, vol. 19(4), pages 687-712, December.
    7. Augenblick, Ned & Cunha, Jesse M. & Dal Bó, Ernesto & Rao, Justin M., 2016. "The economics of faith: using an apocalyptic prophecy to elicit religious beliefs in the field," Journal of Public Economics, Elsevier, vol. 141(C), pages 38-49.
    8. Banerjee, Ritwik & Gupta, Nabanita Datta & Villeval, Marie Claire, 2020. "Feedback spillovers across tasks, self-confidence and competitiveness," Games and Economic Behavior, Elsevier, vol. 123(C), pages 127-170.
    9. Wu, Qin & Bayer, Ralph-C & Lenten, Liam J.A., 2020. "Conditional Pension Funds to Combat Cheating in Sporting Contests: Theory and Experimental Evidence," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 89(C).
    10. Markus Brunner & Andreas Ostermaier, 2019. "Peer Influence on Managerial Honesty: The Role of Transparency and Expectations," Journal of Business Ethics, Springer, vol. 154(1), pages 127-145, January.
    11. Llorente-Saguer, Aniol & Sheremeta, Roman M. & Szech, Nora, 2023. "Designing contests between heterogeneous contestants: An experimental study of tie-breaks and bid-caps in all-pay auctions," European Economic Review, Elsevier, vol. 154(C).
    12. Jeanne Hagenbach & Charlotte Saucet, 2024. "Motivated Skepticism," SciencePo Working papers Main hal-03770685, HAL.
    13. Kai Barron, 2021. "Belief updating: does the ‘good-news, bad-news’ asymmetry extend to purely financial domains?," Experimental Economics, Springer;Economic Science Association, vol. 24(1), pages 31-58, March.
    14. Gächter, Simon & Gerhards, Leonie & Nosenzo, Daniele, 2017. "The importance of peers for compliance with norms of fair sharing," European Economic Review, Elsevier, vol. 97(C), pages 72-86.
    15. Fehr, Dietmar & Rau, Hannes & Trautmann, Stefan T. & Xu, Yilong, 2020. "Inequality, fairness and social capital," European Economic Review, Elsevier, vol. 129(C).
    16. Choo, C.Y. Lawrence & Fonseca, Miguel A. & Myles, Gareth D., 2016. "Do students behave like real taxpayers in the lab? Evidence from a real effort tax compliance experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 124(C), pages 102-114.
    17. Dimant, Eugen, 2015. "On Peer Effects: Behavioral Contagion of (Un)Ethical Behavior and the Role of Social Identity," MPRA Paper 68732, University Library of Munich, Germany.
    18. Vossler, Christian A. & Gilpatric, Scott M., 2018. "Endogenous audits, uncertainty, and taxpayer assistance services: Theory and experiments," Journal of Public Economics, Elsevier, vol. 165(C), pages 217-229.
    19. Martin Kesternich & Andreas Lange & Bodo Sturm, 2018. "On the performance of rule-based contribution schemes under endowment heterogeneity," Experimental Economics, Springer;Economic Science Association, vol. 21(1), pages 180-204, March.
    20. Lorko, Matej & Servátka, Maroš & Zhang, Le, 2019. "Anchoring in project duration estimation," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 49-65.

    More about this item

    Keywords

    algorithm aversion; artificial intelligence; moral discretion; behavioral ethics;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

    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:zbw:espost:249297. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/zbwkide.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.