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Measuring preferences for algorithms — How willing are people to cede control to algorithms?

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  • Ivanova-Stenzel, Radosveta
  • Tolksdorf, Michel

Abstract

We suggest a simple method to elicit individual preferences for algorithms. By altering the monetary incentives for ceding control to the algorithm, the menu-based approach allows for measuring in particular the degree of algorithm aversion. Using an experiment, we elicit preferences for algorithms in an environment with measurable performance accuracy under two conditions — the absence and the presence of information about the algorithm’s performance. Providing such information raises subjects’ willingness to rely on algorithms when ceding control to the algorithm is more costly than trusting in their own assessment. However, algorithms are still underutilized.

Suggested Citation

  • Ivanova-Stenzel, Radosveta & Tolksdorf, Michel, 2024. "Measuring preferences for algorithms — How willing are people to cede control to algorithms?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 112(C).
    • Handle: RePEc:eee:soceco:v:112:y:2024:i:c:s2214804324001071
    DOI: 10.1016/j.socec.2024.102270
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    References listed on IDEAS

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    Cited by:

    1. Gaudeul, Alexia & Giannetti, Caterina, 2025. "Beyond Performance: Exploring trade-offs in the design of financial algorithms," Journal of Behavioral and Experimental Finance, Elsevier, vol. 48(C).
    2. Micha Kaiser & Cass R. Sunstein & Lucia A. Reisch, 2025. "On preferring people to algorithms," Journal of Risk and Uncertainty, Springer, vol. 71(3), pages 245-272, December.
    3. Bernd Irlenbusch, 2026. "Human Trust in AI: Evidence from Experimental Economics," ECONtribute Discussion Papers Series 417, University of Bonn and University of Cologne, Germany.
    4. Hans-Theo Normann & Nina Ruli'e & Olaf Stypa & Tobias Werner, 2025. "Delegate Pricing Decisions to an Algorithm? Experimental Evidence," Papers 2510.27636, arXiv.org.
    5. Radosveta Ivanova-Stenzel & Michel Tolksdorf, 2025. "Delegating in the Age of AI: Preferences for Decision Autonomy," Rationality and Competition Discussion Paper Series 558, CRC TRR 190 Rationality and Competition.

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    Keywords

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    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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