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Trust in Humans and Robots: Economically Similar but Emotionally Different

Author

Listed:
  • Timothy Shields

    (Economic Science Institute, Chapman University
    Argyros School of Business and Economics, Chapman University)

  • Eric Schniter

    (Economic Science Institute, Chapman University
    Argyros School of Business and Economics, Chapman University)

  • Daniel Sznycer

    (Department of Psychology, University of Montreal)

Abstract

Trust-based interactions with robots are increasingly common in the marketplace, workplace, on the road, and in the home. However, a looming concern is that people may not trust robots as they do humans. While trust in fellow humans has been studied extensively, little is known about how people extend trust to robots. Here we compare trust-based investments and emotions from across three nearly identical economic games: human-human trust games, human-robot trust games, and human-robot trust games where the robot decision impacts another human. Robots in our experiment mimic humans: they are programmed to make reciprocity decisions based on previously observed behaviors by humans in analogous situations. We find that people invest similarly in humans and robots. By contrast, the social emotions elicited by the interactions (but not non-social emotions) differed across human and robot trust games, and did so lawfully. Emotional reactions depended on how one’s trust game decision interacted with the partnered agent’s decision, and whether another person was affected economically and emotionally.

Suggested Citation

  • Timothy Shields & Eric Schniter & Daniel Sznycer, 2018. "Trust in Humans and Robots: Economically Similar but Emotionally Different," Working Papers 18-22, Chapman University, Economic Science Institute.
  • Handle: RePEc:chu:wpaper:18-22
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    File URL: https://digitalcommons.chapman.edu/esi_working_papers/282/
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    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. Brice Corgnet, 2023. "An Experimental Test of Algorithmic Dismissals," Working Papers 23-02, Chapman University, Economic Science Institute.
    4. Luca Delle Foglie & Stefano Papa & Giancarlo Spagnolo, 2025. "Rage Against the Machine or Humans?," CEIS Research Paper 593, Tor Vergata University, CEIS, revised 21 Feb 2025.
    5. Corgnet, Brice & Hernán-González, Roberto & Mateo, Ricardo, 2023. "Peer effects in an automated world," Labour Economics, Elsevier, vol. 85(C).
    6. Caterina Cruciani & Carlo Romano Marcello Alessandro Santagiustina & Costanza Sartoris & Massimo Warglien, 2024. "Survey on experiments about trust and collaborative vs conflictual language," Sciences Po Economics Publications (main) hal-04922031, HAL.
    7. Zarifis, Alex & Cheng, Xusen, 2022. "A model of trust in Fintech and trust in Insurtech: How Artificial Intelligence and the context influence it," Journal of Behavioral and Experimental Finance, Elsevier, vol. 36(C).
    8. Bejarano, Hernán & Gillet, Joris & Rodriguez-Lara, Ismael, 2021. "Trust and trustworthiness after negative random shocks," Journal of Economic Psychology, Elsevier, vol. 86(C).
    9. Xiangdong Qin & Siyu Wang & Mike Zhiren Wu & Xuechun Feng, 2025. "From Adam Smith to artificial intelligence: an experimental exploration of emotion in humanomics," Public Choice, Springer, vol. 202(3), pages 383-399, March.
    10. 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).
    11. 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).
    12. Murakami, Yutaro & Taguchi, Satoshi, 2025. "How gender and prosociality affect machine interaction in tax compliance: A game-theoretic experiment," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 116(C).
    13. Tse, Tiffany Tsz Kwan & Hanaki, Nobuyuki & Mao, Bolin, 2024. "Beware the performance of an algorithm before relying on it: Evidence from a stock price forecasting experiment," Journal of Economic Psychology, Elsevier, vol. 102(C).
    14. Sofianos, Andis, 2022. "Self-reported & revealed trust: Experimental evidence," Journal of Economic Psychology, Elsevier, vol. 88(C).
    15. Strobel, Christina, 2025. "The impact of process automation on performance," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 117(C).
    16. Jin, Shan & Yan, Sibo & Zhang, Xiaomeng, 2025. "Measuring trust across countries: Inconsistencies between experiments and surveys," Economics Letters, Elsevier, vol. 248(C).
    17. Yuka Okada & Mitsuhiko Kimoto & Takamasa Iio & Katsunori Shimohara & Masahiro Shiomi, 2023. "Two is better than one: Apologies from two robots are preferred," PLOS ONE, Public Library of Science, vol. 18(2), pages 1-17, February.
    18. Roman Lukyanenko & Wolfgang Maass & Veda C. Storey, 2022. "Trust in artificial intelligence: From a Foundational Trust Framework to emerging research opportunities," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 1993-2020, December.

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    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • D64 - Microeconomics - - Welfare Economics - - - Altruism; Philanthropy; Intergenerational Transfers
    • L5 - Industrial Organization - - Regulation and Industrial Policy

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