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Elaborating Team Roles for Artificial Intelligence-based Teammates in Human-AI Collaboration

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  • Dominik Siemon

    (LUT University)

Abstract

The increasing importance of artificial intelligence (AI) in everyday work also means that new insights into team collaboration must be gained. It is important to research how changes in team composition affect joint work, as previous theories and insights on teams are based on the knowledge of pure human teams. Especially, when AI-based systems act as coequal partners in collaboration scenarios, their role within the team needs to be defined. With a multi-method approach including a quantitative and a qualitative study, we constructed four team roles for AI-based teammates. In our quantitative survey based on existing team role concepts (n = 1.358), we used exploratory and confirmatory factor analysis to construct possible roles that AI-based teammates can fulfill in teams. With nine expert interviews, we discussed and further extended our initially identified team roles, to construct consistent team roles for AI-based teammates. The results show four consistent team roles: the coordinator, creator, perfectionist and doer. The new team roles including their skills and behaviors can help to better design hybrid human-AI teams and to better understand team dynamics and processes.

Suggested Citation

  • Dominik Siemon, 2022. "Elaborating Team Roles for Artificial Intelligence-based Teammates in Human-AI Collaboration," Group Decision and Negotiation, Springer, vol. 31(5), pages 871-912, October.
    • Handle: RePEc:spr:grdene:v:31:y:2022:i:5:d:10.1007_s10726-022-09792-z
    DOI: 10.1007/s10726-022-09792-z
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    References listed on IDEAS

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    1. Broekhuizen, Thijs & Dekker, Henri & de Faria, Pedro & Firk, Sebastian & Nguyen, Dinh Khoi & Sofka, Wolfgang, 2023. "AI for managing open innovation: Opportunities, challenges, and a research agenda," Journal of Business Research, Elsevier, vol. 167(C).
    2. Henner Gimpel & Vanessa Graf-Seyfried & Robert Laubacher & Oliver Meindl, 2023. "Towards Artificial Intelligence Augmenting Facilitation: AI Affordances in Macro-Task Crowdsourcing," Group Decision and Negotiation, Springer, vol. 32(1), pages 75-124, February.
    3. Buxmann, Peter & Ellenrieder, Sara, 2024. "Unlocking AI’s Potential : Human Collaboration as the Catalyst," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 149346, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).

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