The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Situation awareness-based agent transparency and human-autonomy teaming effectiveness
Open accessAbstract
Effective collaboration between humans and agents depends on humans maintaining an appropriate understanding of and calibrated trust in the judgment of their agent counterparts. The Situation Awareness-based Agent Transparency (SAT) model was proposed to support human awareness in human–agent teams. As agents transition from tools to artificial teammates, an expansion of the model is necessary to support teamwork paradigms, which require bidirectional transparency. We propose that an updated model can better inform human–agent interaction in paradigms involving more advanced agent teammates. This paper describes the model's use in three programmes of research, which exemplify the utility of the model in different contexts – an autonomous squad member, a mediator between a human and multiple subordinate robots, and a plan recommendation agent. Through this review, we show that the SAT model continues to be an effective tool for facilitating shared understanding and proper calibration of trust in human–agent teams.
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Citations
Cites
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Trust in Automation: Designing for Appropriate Reliance
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“Automation bias has been described as a manifestation of inappropriate trust, i.e. overtrust (Parasura-man, Molloy, and Singh 1993), and can be encouraged by highly reliable systems, as well as operator inexperience and high workload (Chen and Barnes 2010; Lee and See 2004).”
BackgroundHumans 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
Performance Consequences of Automation-Induced 'Complacency'
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Intelligent agent transparency in human–agent teaming for multi-UxV management
Mercado, J. E., Rupp, M. A., Chen, J. Y. C., Barnes, M. J., Barber, D., & Procci, K. (2016) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720815621206 · Cited by 403
Self-citationMcGuirl, J. M., & Sarter, N. B. (2006) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872006779166334 · Cited by 212
Transparency in a Human-Machine Context: Approaches for Fostering Shared Awareness/Intent
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Cited by
Stephanidis, C., Salvendy, G., Antona, M., Chen, J. Y. C., Dong, J., Duffy, V. G., Fang, X., Fidopiastis, C., Fragomeni, G., Fu, L. P., et al. (2019) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2019.1619259 · Cited by 524
Self-citationTowards 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
Tossell, C. C., Tenhundfeld, N. L., Momen, A., Cooley, K., & de Visser, E. J. (2024) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2024.3355015 · Cited by 218
Kunze, A., Summerskill, S. J., Marshall, R., & Filtness, A. J. (2019) · Ergonomics · doi:10.1080/00140139.2018.1547842 · Cited by 165
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
Metadata
- Authors
- Chen, J. Y. C., Lakhmani, S. G., Stowers, K., Selkowitz, A. R., Wright, J. L., & Barnes, M.
- Venue
- Theoretical Issues in Ergonomics Science
- Publisher
- Informa UK Limited
- Published
- 2018-02-23
- Volume
- 19
- Issue
- 3
- Pages
- 259-282
- ISSN
- 1463-922X (ISSN-L)
- 1464-536X
- OpenAlex
- W2791890170
- Cited by
- 351
- References
- 8
- FWCI
- 33.19
- Type
- journal article
- Language
- en
- Open access
- hybrid
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