Towards a Theory of Longitudinal Trust Calibration in Human–Robot Teams
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Trust is a dynamic variable that can change over time.
“trust is a dynamic variable that can change over time”
From Toward Quantifying Trust Dynamics: How People Adjust Their Trust After Moment-to-Moment Interaction With Automation (2023) · cites this paper as de Visser et al., 2020
With few exceptions, there is little understanding of how trust strengthens or decays due to moment-to-moment interactions with automation.
“With few exceptions, we have little understanding of how trust strengthens or decays due to moment-to-moment interactions with automation”
From Toward Quantifying Trust Dynamics: How People Adjust Their Trust After Moment-to-Moment Interaction With Automation (2023) · cites this paper as de Visser et al., 2020
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“Even though trust between humans and robots may not be tantamount to trust among humans [87], we may still draw insights from human–human trust development frameworks [29].”
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“Previous research on trust in HRTs has primarily focused on identifying initial trust states and potential determinants [9,53,126].”
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“Many examples exist of accidents caused by overtrust [6,45,111,133].”
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“Many examples exist of accidents caused by overtrust [6,45,111,133].”
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“These systems are a special form of adaptive automation [10,42,63,78,129] that can measure the trust state of a human and then adapt their behavior accordingly to provide a positive impact on team performance.”
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“…of the operator [38] \ Convey uncertainty directly Conveying uncertainty directly by providing facial cues [8] or machine confidence indicators [36,57,62,86,97,157] \ Provide verification methods Offering methods for detailed verification of the system’s behavior and performance to reduce the…”
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Evaluating Effects of User Experience and System Transparency on Trust in Automation
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“To avoid any such loss due to over-or under-trust, trust needs to be calibrated [74] or warranted [53], which describes “how well trust matches the true capabilities of the automation” [74, p. 57] (see also [28]).”
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“With few exceptions, we have little understanding of how trust strengthens or decays due to moment-to-moment interactions with automation (de Visser et al., 2020; Guo & Yang, 2020; Yang, Guo, & Schemanske, To appear; Yang, Unhelkar, Li, & Shah, 2017).”
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- Authors
- de Visser, E. J., Peeters, M. M. M., Jung, M. F., Kohn, S., Shaw, T. H., Pak, R., & Neerincx, M. A.
- Affiliations
- Netherlands Organisation for Applied Scientific Research (NL)
- Cornell University (US)
- George Mason University (US)
- Clemson University (US)
- ORCID
- Venue
- International Journal of Social Robotics
- Published
- 2019-11-23
- Volume
- 12
- Issue
- 2
- Pages
- 459-478
- ISSN
- 1875-4791 (ISSN-L)
- 1875-4805
- OpenAlex
- W2989822567
- Cited by
- 447
- References
- 26
- Citations by year
- 2026: 91 · 2025: 100 · 2024: 80 · 2023: 67 · 2022: 58 · 2021: 30 · 2020: 21
- FWCI
- 34.24
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Social Robotics (publishedVersion)
- TNO Repository (submittedVersion)
- Repository hosted by TU Delft Library (TU Delft) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- Air Force Office of Scientific Research (16RT0881, FA9550-18-1-0455)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Social Sciences › Psychology › Social Psychology › Team Dynamics and Performance
- Keywords
- human-robot teams, trust calibration, relationship equity, overtrust, trust repair, transparency, explanation, employment contracts, human-robot collaboration, social robots
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