The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Associations between Trust Dynamics and Personal Characteristics
Abstract
While personal characteristics influence people’s snapshot trust towards autonomous systems, their relationships with trust dynamics remain poorly understood. To address this gap, we conducted a human-subject experiment involving 130 participants performing a simulated surveillance task aided by an automated threat detector. A comprehensive pre-experimental survey gathered participants’ personal characteristics measured in 12 constructs and 28 dimensions. We clustered participants’ trust dynamics into three groups, namely Bayesian decision-makers, disbelievers, and oscillators. Subsequently, we identified their distinctive attributes regarding personal characteristics. Results showed that the clusters differ in seven personal characteristics (masculinity, positive affect, extraversion, neuroticism, intellect, performance expectancy, high expectations). Our findings provide implications for designing specialized trust prediction algorithms tailored to each type of trust dynamics and trust-aware agents.
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“Trust can rapidly change with a single interaction (Chung & Yang, 2024; Yang et al., 2023).”
From Calibrating Trust, Reliance and Dependence in Variable-Reliability Automation (2024) · cites this paper as Chung & Yang, 2024
Citations
Cites
A Meta-Analysis of Factors Affecting Trust in Human-Robot Interaction
Hancock, P. A., Billings, D. R., Schaefer, K. E., Chen, J. Y. C., de Visser, E. J., & Parasuraman, R. (2011) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720811417254 · Cited by 2,051 · cited 2×
“To identify relevant factors that affect users’ trust in autonomy, we conducted a thorough review of key literature review and meta-analysis papers [4]–[9].”
BackgroundMethodHuman–Robot Interaction: Status and Challenges
Sheridan, T. B. (2016) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720816644364 · Cited by 786
Manzey, D., Reichenbach, J., & Onnasch, L. (2012) · Journal of Cognitive Engineering and Decision Making · doi:10.1177/1555343411433844 · Cited by 277
Effects of Anthropomorphism and Accountability on Trust in Human Robot Interaction
Natarajan, M., & Gombolay, M. (2020) · Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction · doi:10.1145/3319502.3374839 · Cited by 248
Resilient Chatbots: Repair Strategy Preferences for Conversational Breakdowns
Ashktorab, Z., Jain, M., Liao, Q. V., & Weisz, J. D. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300484 · Cited by 224
Evaluating Effects of User Experience and System Transparency on Trust in Automation
Yang, X. J., Unhelkar, V. V., Li, K., & Shah, J. A. (2017) · Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction · doi:10.1145/2909824.3020230 · Cited by 208
Self-citationYang, X. J., Schemanske, C., & Searle, C. (2023) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208211034716 · Cited by 132 · cited 2×
“One line of research on trust dynamics explores how trust is formed, violated, and recovered when humans interact with autonomous and robotic agents [10], [11], [13]–[15].”
BackgroundMethodSelf-citationEsterwood, C., & Jr, L. P. R. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.107658 · Cited by 98
Owning Mistakes Sincerely: Strategies for Mitigating AI Errors
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“Numerous studies have demonstrated the effectiveness of different trust repair strategies aimed at restoring trust following violations [16], including apologies [17]–[19], denials [18], explanations [17], [20], [21], and promises [22].”
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Cited by
Sorted by citations
Kim, J. Y., Lester, C., & Yang, X. J. (2025) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208251326795 · Cited by 21
Self-citationCalibrating Trust, Reliance and Dependence in Variable-Reliability Automation
Holland, C., Perry, G., & Neyedli, H. F. (2024) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/10711813241277531 · Cited by 8
Metadata
- Authors
- Chung, H., & Yang, X. J.
- Affiliations
- University of Michigan,Department of Industrial and Operations Engineering,Ann Arbor,USA
- Venue
- 2024 IEEE 4th International Conference on Human-Machine Systems (ICHMS)
- Publisher
- IEEE
- Published
- 2024-05-15
- Pages
- 1-6
- Cited by
- 10
- References
- 11
- Funders
- National Science Foundation
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