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We and It: An interdisciplinary review of the experimental evidence on how humans interact with machines

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  • Chugunova, Marina
  • Sele, Daniela

Abstract

Today, humans interact with automation frequently and in a variety of settings ranging from private to professional. Their behavior in these interactions has attracted considerable research interest across several fields, with sometimes little exchange among them and seemingly inconsistent findings. In this article, we review 138 experimental studies on how people interact with automated agents, that can assume different roles. We synthesize the evidence, suggest ways to reconcile inconsistencies between studies and disciplines, and discuss organizational and societal implications. The reviewed studies show that people react to automated agents differently than they do to humans: In general, they behave more rationally, and seem less prone to emotional and social responses, though this may be mediated by the agents’ design. Task context, performance expectations and the distribution of decision authority between humans and automated agents are all factors that systematically impact the willingness to accept automated agents in decision-making - that is, humans seem willing to (over-)rely on algorithmic support, yet averse to fully ceding their decision authority. The impact of these behavioral regularities for the deliberation of the benefits and risks of automation in organizations and society is discussed.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:soceco:v:99:y:2022:i:c:s2214804322000714
    DOI: 10.1016/j.socec.2022.101897
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    Cited by:

    1. Daniela Sele & Marina Chugunova, 2023. "Putting a Human in the Loop: Increasing Uptake, but Decreasing Accuracy of Automated Decision-Making," Rationality and Competition Discussion Paper Series 438, CRC TRR 190 Rationality and Competition.
    2. Liu, Fanjue & Lee, Yu-Hao, 2024. "Virtually responsible? Attribution of responsibility toward human vs. virtual influencers and the mediating role of mind perception," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
    3. Dreyfuss, Bnaya & Heffetz, Ori & Hoffman, Guy & Ishai, Guy & Kshirsagar, Alap, 2024. "Additive vs. subtractive earning in shared human-robot work environments," Journal of Economic Behavior & Organization, Elsevier, vol. 217(C), pages 692-704.
    4. Fabian Dvorak & Regina Stumpf & Sebastian Fehrler & Urs Fischbacher, 2024. "Generative AI Triggers Welfare-Reducing Decisions in Humans," Papers 2401.12773, arXiv.org.
    5. Ivan Ðula & Tabea Berberena & Ksenia Keplinger & Maria Wirzberger, 2024. "From challenges to opportunities: navigating the human response to automated agents in the workplace," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    6. Maggioni, Mario A. & Rossignoli, Domenico, 2023. "If it looks like a human and speaks like a human ... Communication and cooperation in strategic Human–Robot interactions," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 104(C).
    7. Vomberg, Arnd & Schauerte, Nico & Krakowski, Sebastian & Ingram Bogusz, Claire & Gijsenberg, Maarten J. & Bleier, Alexander, 2023. "The cold-start problem in nascent AI strategy: Kickstarting data network effects," Journal of Business Research, Elsevier, vol. 168(C).
    8. Gorny, Paul M. & Groos, Eva & Strobel, Christina, 2024. "Do Personalized AI Predictions Change Subsequent Decision-Outcomes? The Impact of Human Oversight," MPRA Paper 121065, University Library of Munich, Germany.
    9. Lorenzo Cominelli & Federico Galatolo & Caterina Giannetti & Cristiano Ciaccio & Felice Dell’Orletta & Philipp Chaposkvi & Giulia Venturi, 2024. "Teaming Up with Artificial Agents in Non-routine Analytical Tasks," Discussion Papers 2024/314, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.

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    More about this item

    Keywords

    Automation; Human-computer interaction; Human-machine interaction; Algorithmic decision making; Experimental evidence; Literature review;
    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
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General

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