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
Abstract
Abstract : Autonomous agents have been increasingly used for military operations (e.g., casualty extraction, explosive detection and disposals, reconnaissance and surveillance, supply transportation, building clearing, and firefighting), search and rescue, transportation safety, space exploration, farming, and many other purposes yet to emerge (Barnes and Evans, 2010; Greenemeier, 2010; Jones and Schmidlin, 2011; Morals and the Machine, 2012; Murphy and Burke, 2010; Osborn, 2011; Purdy, 2008; Singer, 2010). As these agents become more sophisticated and independent, it is critical for their human counterparts to understand their behaviors, the reasoning process behind those behaviors, and the expected outcomes to properly calibrate their trust in the systems and make appropriate decisions (de Visser et al., 2014; Lee and See, 2004). Indeed, past studies have shown that human operators sometimes question the accuracy and effectiveness of agents actions due to the operators difficulties understanding the state/status of the agent (Bitan and Meyer, 2007; Seppelt and Lee, 2007; Stanton et al., 2007) and the rationales behind the behaviors (Linegang et al., 2006). These limitations can be substantial impediments to overall system and task performance.
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Citations
Cites
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
Conditions for intuitive expertise: A failure to disagree.
Kahneman, D., & Klein, G. (2009) · American Psychologist · doi:10.1037/a0016755 · Cited by 2,443
Representations in Distributed Cognitive Tasks
Zhang, J., & Norman, D. A. (1994) · Cognitive Science · doi:10.1207/s15516709cog1801_3 · Cited by 1,203 · cited 2×
“One strategy for conveying this information to the operator is representational analysis, where different variables and representations are identified, based on the task hierarchy, and placed into context, i.e., displayed relative to data limits or ranges (Zhang and Norman, 1994).”
Ecological interface design: theoretical foundations
Vicente, K. J., & Rasmussen, J. (1992) · IEEE Transactions on Systems, Man and Cybernetics · doi:10.1109/21.156574 · Cited by 1,084
The Ecology of Human-Machine Systems II: Mediating 'Direct Perception' in Complex Work Domains
Vicente, K. J., & Rasmussen, J. (1990) · Ecological Psychology · doi:10.1207/s15326969eco0203_2 · Cited by 457 · cited 1×
“The effectiveness of EIDs for human-agent interaction has been investigated in several studies (Cummings and Bruni, 2010; Furukawa et al., 2004; Furukawa and Parasuraman, 2003; Kirlik, 1995; Seppelt and Lee, 2007; Vicente and Rasmussen, 1990; Vicente and Rasmussen, 1992; Vicente, 2002; Woods, 1991).”
McGuirl, 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
Lyons, J. B., & Havig, P. R. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-07458-0_18 · Cited by 96
Dong, X., & Hayes, C. C. (2012) · Journal of Cognitive Engineering and Decision Making · doi:10.1177/1555343411432338 · Cited by 36
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Explanation in artificial intelligence: Insights from the social sciences
Miller, T. (2019) · Artificial Intelligence · doi:10.1016/j.artint.2018.07.007 · Cited by 5,302
Schaefer, K. E., Chen, J. Y. C., Szalma, J. L., & Hancock, P. A. (2016) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720816634228 · Cited by 768
Self-citationIntelligent 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-citationKraus, J., Scholz, D., Stiegemeier, D., & Baumann, M. (2020) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720819853686 · Cited by 276
Weitz, K., Schiller, D., Schlagowski, R., Huber, T., & André, E. (2019) · Proceedings of the 19th ACM International Conference on Intelligent Virtual Agents · doi:10.1145/3308532.3329441 · Cited by 136
I can do better than your AI: expertise and explanations
Schaffer, J., O'Donovan, J., Michaelis, J., Raglin, A., & Höllerer, T. (2019) · Proceedings of the 24th International Conference on Intelligent User Interfaces · doi:10.1145/3301275.3302308 · Cited by 119
Explainable goal-driven agents and robots-a comprehensive review
Sado, F., Loo, C. K., Liew, W. S., Kerzel, M., & Wermter, S. (2023) · ACM Computing Surveys · doi:10.1145/3564240 · Cited by 79
“SAT is an agent transparency model for enhancing an operator’s situational awareness [60] in the agent’s environment [23, 39].”
Gutzwiller, R. S., Chiou, E. K., Craig, S. D., Lewis, C. M., Lematta, G. J., & Hsiung, C.-P. (2019) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1071181319631201 · Cited by 54
Human-machine plan conflict and conflict resolution in a visual search task
Pan, Y., & Xu, J. (2025) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2024.103377 · Cited by 54
Lai, H.-Y., Chen, C.-H., Khoo, L.-P., & Zheng, P. (2019) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2019.01.009 · Cited by 32
How to Achieve Explainability and Transparency in Human AI Interaction
Hois, J., Theofanou-Fuelbier, D., & Junk, A. J. (2019) · Communications in Computer and Information Science · doi:10.1007/978-3-030-23528-4_25 · Cited by 31
Insights into Human-Agent Teaming: Intelligent Agent Transparency and Uncertainty
Stowers, K., Kasdaglis, N., Rupp, M., Chen, J., Barber, D., & Barnes, M. (2017) · Advances in Intelligent Systems and Computing · doi:10.1007/978-3-319-41959-6_13 · Cited by 28
Self-citationCalibrating Reliance on Automated Advice: Transparency and Trust Calibration Feedback
Tatasciore, M., & Loft, S. (2025) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2025.2487861 · Cited by 20
A study of dynamic information display and decision-making in abstract trust games
Schaffer, J., O’Donovan, J., Marusich, L., Yu, M., Gonzalez, C., & Höllerer, T. (2018) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2018.01.002 · Cited by 10
McMahon, G., Akash, K., Reid, T., & Jain, N. (2020) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2021.04.113 · Cited by 10
Metadata
- Authors
- Chen, J. Y., Procci, K., Boyce, M., Wright, J., Garcia, A., & Barnes, M.
- Publisher
- Defense Technical Information Center
- Published
- 2014-04-01
- OpenAlex
- W3404557
- Cited by
- 293
- References
- 8
- Type
- report
- Language
- en
- Open access
- closed
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