PreprintCited by 5Human-Automation Interaction and SafetyExperimental Behavioral Economics StudiesTeam Dynamics and Performance

Super Mario Meets AI: The Effects of Automation on Team Performance and Coordination in a Videogame Experiment

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Dell'Acqua, Fabrizio, Kogut, Bruce, Perkowski, Patryk·2020·SSRN Electronic Journal

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Registry

Crossref · 10.2139/ssrn.3746564

Cites

55 of 55 references verified0 citation errors · 0 not checkable

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  • The introduction of an AI agent makes coordination more difficult for human players and creates less trust among members of the team.

    “The authors argue the introduction of the AI agent makes coordination more difficult for human players—and also creates less trust among members of the team.”

    From Can Generative AI improve social science? (2024) · cites this paper as [28]

  • In a collaborative cooking game, human agents perform more poorly when an AI agent is on their team compared to an all-human team.

    “When an AI agent is introduced in a team setting, the researchers find that human agents perform more poorly when the agent is on their team, compared to an all-human team.”

    From Can Generative AI improve social science? (2024) · cites this paper as [28]

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Authors
Dell'Acqua, F., Kogut, B., & Perkowski, P.
Affiliations
Columbia University (US)
Venue
SSRN Electronic Journal
Publisher
Elsevier BV
Published
2020
ISSN
1556-5068 (ISSN-L)
OpenAlex
W3129865218
Cited by
5
References
55
Citations by year
2024: 2 · 2022: 1 · 2020: 2
Type
posted content
Language
en
Open access
Locations
SSRN Electronic Journal (publishedVersion)
Topics
  • Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
  • Social Sciences › Safety Research › Experimental Behavioral Economics Studies
  • Social Sciences › Psychology › Social Psychology › Team Dynamics and Performance
Keywords
artificial intelligence adoption, automation, team performance, team coordination, human-machine interaction, Nintendo Switch, team trust, effort provision, coordination failure, skill distribution, organizational performance

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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