The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
From ‘automation’ to ‘autonomy’: the importance of trust repair in human–machine interaction
Abstract
Modern interactions with technology are increasingly moving away from simple human use of computers as tools to the establishment of human relationships with autonomous entities that carry out actions on our behalf. In a recent commentary, Peter Hancock issued a stark warning to the field of human factors that attention must be focused on the appropriate design of a new class of technology: highly autonomous systems. In this article, we heed the warning and propose a human-centred approach directly aimed at ensuring that future human-autonomy interactions remain focused on the user's needs and preferences. By adapting literature from industrial psychology, we propose a framework to infuse a unique human-like ability, building and actively repairing trust, into autonomous systems. We conclude by proposing a model to guide the design of future autonomy and a research agenda to explore current challenges in repairing trust between humans and autonomous systems. Practitioner Summary: This paper is a call to practitioners to re-cast our connection to technology as akin to a relationship between two humans rather than between a human and their tools. To that end, designing autonomy with trust repair abilities will ensure future technology maintains and repairs relationships with their human partners.
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“Despite their positioning on the same unidimensional continuum, however, automation and autonomy can be studied as different phenomena (de Visser et al., 2018; Hancock, 2017).”
From Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature (2022) · cites this paper as de Visser et al., 2018
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Cites
Trust, Reciprocity, and Social History
Berg, J., Dickhaut, J., & McCabe, K. (1995) · Games and Economic Behavior · doi:10.1006/game.1995.1027 · Cited by 5,548
Humans and automation: Use, misuse, disuse, abuse
Parasuraman, R., & Riley, V. (1997) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872097778543886 · Cited by 4,554
A model for types and levels of human interaction with automation
Parasuraman, R., Sheridan, T. B., & Wickens, C. D. (2000) · IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans · doi:10.1109/3468.844354 · Cited by 4,195 · cited 1×
“To solve this problem, Parasuraman and colleagues (Parasuraman and Hancock 1999; Parasuraman, Sheridan, and Wickens 2000) proposed fuzzy signal detection and Bayesian approaches to the mapping of responses to the state of the world.”
Dehumanization: An integrative review
Haslam, N. (2006) · Personality and Social Psychology Review · doi:10.1207/s15327957pspr1003_4 · Cited by 2,919 · cited 5×
“…and have addressed both sides of the interaction: on the role of apologies from the transgres-sor’s perspective (Dirks et al. 2011; Kim et al. 2004, 2006; Schweitzer, Hershey, and Bradlow 2006) and on the factors that stimulate forgiveness from the victim’s perspective, such as likeability, blame…”
InfluentialTrust in Automation: Integrating Empirical Evidence on Factors That Influence Trust
Hoff, K. A., & Bashir, M. (2015) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720814547570 · Cited by 2,817
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×
“unique implications for human–robot teams in the urban search and rescue domain as highlighted in our vignette (Hancock et al. 2011; de Visser, Pak, and Neerincx 2017).”
BackgroundSwift Trust and Temporary Groups
Meyerson, D., Weick, K. E., & Kramer, R. M. (1996) · Trust in Organizations: Frontiers of Theory and Research · doi:10.4135/9781452243610.n9 · Cited by 1,982 · cited 1×
“For instance, swift trust is the notion that technical experts, such as surgeons, quickly establish trust by rapidly recognising expert behaviour, such as hand movements (Meyerson, Weick, and Kramer 1996).”
Is there a “Big Five” in Teamwork?
Salas, E., Sims, D. E., & Burke, C. S. (2005) · Small Group Research · doi:10.1177/1046496405277134 · Cited by 1,930
The role of trust in automation reliance
Dzindolet, M. T., Peterson, S. A., Pomranky, R. A., Pierce, L. G., & Beck, H. P. (2003) · International Journal of Human-Computer Studies · doi:10.1016/s1071-5819(03)00038-7 · Cited by 1,276
MUIR, B. M., & MORAY, N. (1996) · Ergonomics · doi:10.1080/00140139608964474 · Cited by 993
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O’Neill, T., McNeese, N., Barron, A., & Schelble, B. (2022) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720820960865 · Cited by 695
Algorithms as work designers: How algorithmic management influences the design of jobs
Parent-Rocheleau, X., & Parker, S. K. (2022) · Human Resource Management Review · doi:10.1016/j.hrmr.2021.100838 · Cited by 512
Towards a Theory of Longitudinal Trust Calibration in Human–Robot Teams
de Visser, E. J., Peeters, M. M. M., Jung, M. F., Kohn, S., Shaw, T. H., Pak, R., & Neerincx, M. A. (2020) · International Journal of Social Robotics · doi:10.1007/s12369-019-00596-x · Cited by 447
Self-citationTrust and reliance on AI — An experimental study on the extent and costs of overreliance on AI
Klingbeil, A., Grützner, C., & Schreck, P. (2024) · Computers in Human Behavior · doi:10.1016/j.chb.2024.108352 · Cited by 450
Xu, W., Dainoff, M. J., Ge, L., & Gao, Z. (2023) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2022.2041900 · Cited by 363
Trusting Automation: Designing for Responsivity and Resilience
Chiou, E. K., & Lee, J. D. (2023) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208211009995 · Cited by 301
Kunze, A., Summerskill, S. J., Marshall, R., & Filtness, A. J. (2019) · Ergonomics · doi:10.1080/00140139.2018.1547842 · Cited by 165
Zhang, R., Duan, W., Flathmann, C., McNeese, N., Freeman, G., & Williams, A. (2023) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3610072 · Cited by 134
Kim, T., & Song, H. (2021) · Telematics and Informatics · doi:10.1016/j.tele.2021.101595 · Cited by 101
Taxonomy of Trust-Relevant Failures and Mitigation Strategies
Tolmeijer, S., Weiss, A., Hanheide, M., Lindner, F., Powers, T. M., Dixon, C., & Tielman, M. L. (2020) · Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction · doi:10.1145/3319502.3374793 · Cited by 103
Esterwood, C., & Jr, L. P. R. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.107658 · Cited by 98
Challenges of human—machine collaboration in risky decision-making
Xiong, W., Fan, H., Ma, L., & Wang, C. (2022) · Frontiers of Engineering Management · doi:10.1007/s42524-021-0182-0 · Cited by 95
Trust repair in human-agent teams: the effectiveness of explanations and expressing regret
Kox, E. S., Kerstholt, J. H., Hueting, T. F., & de Vries, P. W. (2021) · Autonomous Agents and Multi-Agent Systems · doi:10.1007/s10458-021-09515-9 · Cited by 83
Do You Still Trust Me? Human-Robot Trust Repair Strategies
Esterwood, C., & Robert, L. P. (2021) · 2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN) · doi:10.1109/ro-man50785.2021.9515365 · Cited by 75
Deletion, departure, death: Experiences of AI companion loss
Banks, J. (2024) · Journal of Social and Personal Relationships · doi:10.1177/02654075241269688 · Cited by 74
“Others have considered the ways human-human frameworks should or should not be applied to human-machine relations (e.g., de Visser et al., 2018); that prescription somewhat belies the likelihood people will nonetheless see them through the lens of normative human relations and intuit sociality…”
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Tolmeijer, S., Gadiraju, U., Ghantasala, R., Gupta, A., & Bernstein, A. (2021) · Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization · doi:10.1145/3450613.3456817 · Cited by 67
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Johnson, C. J., Demir, M., McNeese, N. J., Gorman, J. C., Wolff, A. T., & Cooke, N. J. (2023) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208211047323 · Cited by 68
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Zhang, X., Lee, S. K., Kim, W., & Hahn, S. (2023) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2023.103031 · Cited by 62
Peng, L., Li, D., Zhang, Z., Zhang, T., Huang, A., Yang, S., & Hu, Y. (2024) · International Journal of Industrial Ergonomics · doi:10.1016/j.ergon.2024.103629 · Cited by 59
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Esterwood, C., & Robert, L. P. (2022) · 2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1109/hri53351.2022.9889535 · Cited by 36
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Albayram, Y., Jensen, T., Khan, M. M. H., Fahim, M. A. A., Buck, R., & Coman, E. (2020) · Proceedings of the 8th International Conference on Human-Agent Interaction · doi:10.1145/3406499.3415064 · Cited by 31
Jensen, T., Khan, M. M. H., Fahim, M. A. A., & Albayram, Y. (2021) · Designing Interactive Systems Conference 2021 · doi:10.1145/3461778.3462102 · Cited by 26
Krystallidou, D., Kersbergen, M. J., de Groot, E., Fluit, C. R. M. G., Kuijer-Siebelink, W., Mertens, F., Oosterbaan-Lodder, S. C. M., Scherpbier, N., Versluis, M. A. C., & Pype, P. (2024) · Medical Teacher · doi:10.1080/0142159x.2024.2314203 · Cited by 26
Kox, E. S., Siegling, L. B., & Kerstholt, J. H. (2022) · International Journal of Social Robotics · doi:10.1007/s12369-022-00871-4 · Cited by 22
A Computational Model of Coupled Human Trust and Self-confidence Dynamics
Williams, K. J., Yuh, M. S., & Jain, N. (2023) · ACM Transactions on Human-Robot Interaction · doi:10.1145/3594715 · Cited by 18
AI apology: a critical review of apology in AI systems
Harland, H., Dazeley, R., Senaratne, H., Vamplew, P., Cruz, F., & Nakisa, B. (2025) · Artificial Intelligence Review · doi:10.1007/s10462-025-11305-8 · Cited by 19
(2021) · doi:10.1145/3461778.3461997 · Cited by 14
The Role of Behavioral Anthropomorphism in Human-Automation Trust Calibration
Jensen, T., Khan, M. M. H., & Albayram, Y. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-50334-5_3 · Cited by 12
Xu, Z., Wang, G., Zhai, S., & Liu, P. (2025) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2023.2176986 · Cited by 12
Explainability in AI: Comparing Human-Like and System-Like Trust Repair Strategies
Konopka, B., & Wiesche, M. (2026) · Information Systems Frontiers · doi:10.1007/s10796-026-10751-1 · Cited by 1
Metadata
- Authors
- de Visser, E. J., Pak, R., & Shaw, T. H.
- Venue
- Ergonomics
- Publisher
- Informa UK Limited
- Published
- 2018-04-09
- Volume
- 61
- Issue
- 10
- Pages
- 1409-1427
- ISSN
- 0014-0139 (ISSN-L)
- 1366-5847
- OpenAlex
- W2793000014
- Cited by
- 398
- References
- 28
- FWCI
- 38.02
- Type
- journal article
- Language
- en
- Open access
- closed
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