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Strategic interactions between humans and artificial intelligence: Lessons from experiments with computer players

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  • March, Christoph

Abstract

Artificial intelligence (AI) is starting to pervade the economic and social life. This renders strategic interactions between humans and artificial agents more and more common. At the same time, experimentalists have increasingly employed computer players as a tool to provide a deeper understanding of strategic interaction in general. What can this strand of research teach us about the strategic behavior of humans interacting with AI? I review 162 experimental studies using computer players. I find that behavior and the outcomes of strategic interaction often change when humans interact with computer players rather than other humans. In particular, humans usually adapt to computer players even absent detailed prior information about them, they often act more selfishly and more rationally in their presence, and they apply different cognitive processes. Moreover, while humans are able to exploit computer players following simple algorithms, they are also vulnerable to exploitation by more sophisticated ones. Conversely, computer players may also enhance efficiency. I suggest several directions for future research.

Suggested Citation

  • March, Christoph, 2021. "Strategic interactions between humans and artificial intelligence: Lessons from experiments with computer players," Journal of Economic Psychology, Elsevier, vol. 87(C).
  • Handle: RePEc:eee:joepsy:v:87:y:2021:i:c:s0167487021000593
    DOI: 10.1016/j.joep.2021.102426
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    2. repec:wyi:journl:002151 is not listed on IDEAS
    3. Shachat, Jason & Swarthout, J. Todd, 2012. "Learning about learning in games through experimental control of strategic interdependence," Journal of Economic Dynamics and Control, Elsevier, vol. 36(3), pages 383-402.
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    More about this item

    Keywords

    Literature review; Experiments; Computer players; Artificial intelligence; Strategic interaction;
    All these keywords.

    JEL classification:

    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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