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.
Authors
- Myrthe L. Tielman (ORCID: https://orcid.org/0000-0002-7826-5821)
- Carolina Centeio Jorge (ORCID: https://orcid.org/0000-0002-6937-5359)
- Francesco Frattolillo (ORCID: https://orcid.org/0000-0002-2040-3355)
- Morgan E Bailey (ORCID: https://orcid.org/0009-0006-2626-1323)
- Anna-Sophie Ulfert
- André Meyer-Vitali
Institutions
- 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)
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