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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Citations
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Cited by
Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature
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
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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
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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