Trust in Human-AI Interaction: Scoping Out Models, Measures, and Methods
Open accessAbstract
Trust has emerged as a key factor in people's interactions with AI-infused systems. Yet, little is known about what models of trust have been used and for what systems: robots, virtual characters, smart vehicles, decision aids, or others. Moreover, there is yet no known standard approach to measuring trust in AI. This scoping review maps out the state of affairs on trust in human-AI interaction (HAII) from the perspectives of models, measures, and methods. Findings suggest that trust is an important and multi-faceted topic of study within HAII contexts. However, most work is under-theorized and under-reported, generally not using established trust models and missing details about methods, especially Wizard of Oz. We offer several targets for systematic review work as well as a research agenda for combining the strengths and addressing the weaknesses of the current literature.
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Laypersons’ perceptions and misconceptions of AI-chatbots: a systematic review
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Effective Continuous Quantitative Measures for End-to-End AI Guardrails
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- Authors
- Ueno, T., Sawa, Y., Kim, Y., Urakami, J., Oura, H., & Seaborn, K.
- Affiliations
- Tokyo Institute of Technology (JP)
- School of Engineering, Tokyo Institute of Technology, Japan
- Tokyo University of Science (JP)
- Venue
- Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2022-04-27
- Pages
- 1-7
- OpenAlex
- W4225095662
- Cited by
- 91
- References
- 56
- Citations by year
- 2026: 29 · 2025: 25 · 2024: 30 · 2023: 7
- FWCI
- 29.85
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Keywords
- trust in AI, human-AI interaction, trust model, trust measurement, trust in robots, virtual characters, intelligent vehicles, decision aids, Wizard of Oz, research agenda
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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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