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Rage against the machine: Automation in the moral domain

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  • Gogoll, Jan
  • Uhl, Matthias

Abstract

The introduction of ever more capable autonomous systems is moving at a rapid pace. The technological progress will enable us to completely delegate to machines processes that were once a prerogative for humans. Progress in fields like autonomous driving promises huge benefits on both economical and ethical scales. Yet, there is little research that investigates the utilization of machines to perform tasks that are in the moral domain. This study explores whether subjects are willing to delegate tasks that affect third parties to machines as well as how this decision is evaluated by an impartial observer. We examined two possible factors that might coin attitudes regarding machine use—perceived utility of and trust in the automated device. We found that people are hesitant to delegate to a machine and that observers judge such delegations in relatively critical light. Neither perceived utility nor trust, however, can account for this pattern. Alternative explanations that we test in a post-experimental survey also do not find support. We may thus observe an aversion per se against machine use in the moral domain.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:soceco:v:74:y:2018:i:c:p:97-103
    DOI: 10.1016/j.socec.2018.04.003
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    References listed on IDEAS

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    Cited by:

    1. Brice Corgnet, 2023. "An Experimental Test of Algorithmic Dismissals," Working Papers 2302, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    2. Nils Köbis & Jean-François Bonnefon & Iyad Rahwan, 2021. "Bad machines corrupt good morals," Nature Human Behaviour, Nature, vol. 5(6), pages 679-685, June.
    3. Back, Camila & Morana, Stefan & Spann, Martin, 2023. "When do robo-advisors make us better investors? The impact of social design elements on investor behavior," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 103(C).
    4. Mahmud, Hasan & Islam, A.K.M. Najmul & Ahmed, Syed Ishtiaque & Smolander, Kari, 2022. "What influences algorithmic decision-making? A systematic literature review on algorithm aversion," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    5. Iván Barreda-Tarrazona & Ainhoa Jaramillo-Gutiérrez & Marina Pavan & Gerardo Sabater-Grande, 2021. "The “Human Factor” in Prisoner’s Dilemma Cooperation," Working Papers 2021/10, Economics Department, Universitat Jaume I, Castellón (Spain).
    6. Chugunova, Marina & Sele, Daniela, 2022. "We and It: An interdisciplinary review of the experimental evidence on how humans interact with machines," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 99(C).
    7. Said Kaawach & Oskar Kowalewski & Oleksandr Talavera, 2023. "Automatic vs Manual Investing: Role of Past Performance," Discussion Papers 23-04, Department of Economics, University of Birmingham.
    8. Till Feier & Jan Gogoll & Matthias Uhl, 2021. "Hiding Behind Machines: When Blame Is Shifted to Artificial Agents," Papers 2101.11465, arXiv.org.
    9. Marina Chugunova & Wolfgang J. Luhan, 2022. "Ruled by robots: Preference for algorithmic decision makers and perceptions of their choices," Working Papers in Economics & Finance 2022-03, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    10. Marina Chugunova & Wolfgang Luhan, 2023. "Ruled by Robots: Preference for Algorithmic Decision Makers and Perceptions of Their Choices," Rationality and Competition Discussion Paper Series 439, CRC TRR 190 Rationality and Competition.
    11. March, Christoph, 2021. "Strategic interactions between humans and artificial intelligence: Lessons from experiments with computer players," Journal of Economic Psychology, Elsevier, vol. 87(C).
    12. 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).

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