Multidisciplinary perspectives on human‑AI team trust

Abstract Human-AI teamwork is no longer a topic of the future. Given the importance of trust in human teams, the question arises how trust functions in human-AI teams. Although trust has long been studied from a human-centred perspective (e.g. in psychology and philosophy), a computational perspective and from the perspective of human trust in AI (e.g. in human-computer interaction), the study of trust in human-AI interaction in a team setting is still a novel field. For this reason, the MULTITTRUST (Multidisciplinary perspectives on Human-AI Team Trust) workshop series was founded. In this paper, we present the main outcomes after three editions. Our contributions are: an overview of the shared language of concepts and definitions; an outline of the main open research challenges; and methodological guidelines for further studies in meaningful human-AI team trust. These three contributions form a foundational roadmap towards a better understanding of trust in human-AI team interactions.

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Publication Details

Journal
Interaction Studies Social Behaviour and Communication in Biological and Artificial Systems
Published
2025-12-31
DOI
https://doi.org/10.1075/is.24048.tie
Citations
1
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
2.44
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article

Multidisciplinary perspectives on human‑AI team trust

Myrthe L. Tielman, Carolina Centeio Jorge, Francesco Frattolillo, Morgan E Bailey et al.
1 citations
Interaction Studies Social Behaviour and Communication in Biological and Artificial Systems
Human-Automation Interaction and Safety
2.44
article

Multidisciplinary perspectives on human‑AI team trust

Myrthe L. Tielman, Carolina Centeio Jorge, Francesco Frattolillo, Morgan E Bailey, Anna-Sophie Ulfert, André Meyer-Vitali
article en
1 citations

Abstract

Abstract Human-AI teamwork is no longer a topic of the future. Given the importance of trust in human teams, the question arises how trust functions in human-AI teams. Although trust has long been studied from a human-centred perspective (e.g. in psychology and philosophy), a computational perspective and from the perspective of human trust in AI (e.g. in human-computer interaction), the study of trust in human-AI interaction in a team setting is still a novel field. For this reason, the MULTITTRUST (Multidisciplinary perspectives on Human-AI Team Trust) workshop series was founded. In this paper, we present the main outcomes after three editions. Our contributions are: an overview of the shared language of concepts and definitions; an outline of the main open research challenges; and methodological guidelines for further studies in meaningful human-AI team trust. These three contributions form a foundational roadmap towards a better understanding of trust in human-AI team interactions.

Interaction Studies Social Behaviour and Communication in Biological and Artificial SystemsVol. 26(2)
Machine Intelligence Research Institute (US), Fraunhofer Institute for Intelligent Analysis and Information Systems (DE), Lamarr Institute for Machine Learning and Artificial Intelligence, Arizona State University (US), University of Glasgow (GB), Delft University of Technology (NL)
Openalex Percentile: Top 8%
Human-Automation Interaction and Safety
2.44
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Multidisciplinary perspectives on human‑AI team trust — Myrthe L. Tielman, Carolina Centeio Jorge, et al. · Interaction Studies Social Behaviour and Communication in Biological and Artificial Systems (2025) | TGRS Research Map | TGRS