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Too Many LLMs to Choose? Design and Trust in Multi-AI Collaboration Systems

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  • Additional Information
    • Publication Date:
      2026
    • Collection:
      ScholarSpace at University of Hawaii at Manoa
    • Abstract:
      Although generative artificial intelligence (GAI) has demonstrated potential in many fields, it still struggles with issues such as limited knowledge and hallucinations. To address these issues, we present a multi-AI collaboration system. Our study takes a multimethod approach, combining design science research (DSR) with quantitative methods. Our aim is to explore the design of effective multi-AI systems and how these affect team trust compared to single-AI setups. We also aim to investigate the differences in users' collaboration experiences between the two models. Our results reveal that multi-AI systems can significantly enhance users' trust in AI, particularly with regard to perceived ability. Users also reported a higher willingness to use multi-AI collaboration and greater satisfaction with it. However, they also noticed more perceived conflict when working with multiple AIs. These findings will help to create more reliable and user-friendly AI collaboration tools, improving the way in which humans and AI can work together effectively.
    • File Description:
      9 pages; application/pdf
    • Relation:
      Proceedings of the 59th Hawaii International Conference on System Sciences; https://hdl.handle.net/10125/111482
    • Online Access:
      https://hdl.handle.net/10125/111482
    • Rights:
      Attribution-NonCommercial-NoDerivatives 4.0 International ; https://creativecommons.org/licenses/by-nc-nd/4.0/
    • Accession Number:
      edsbas.89450EA3