Reimagining Situation Awareness and Option Awareness for Human-Machine Teaming
Abstract
We developed a Co-Awareness Analytic Framework to help ensure satisfactory performance of future teams consisting of humans and intelligent machines operating as peers. This Framework was designed to provide more precision than current tools to analyze the interactions among tasks, task environments, and the capabilities and dependencies among teams of humans and intelligent machines. A key aspect of this framework is reimagined definitions of situation awareness (SA) and option awareness (OA) so that they apply to both humans and machines, rather than defining them in purely cognitive terms that can only be applied to humans. Having appropriate SA and OA has been shown to benefit teams of humans, and there is a presumption that SA/OA will also benefit human-machine teams (HMTs). It is difficult to create requirements for, and subsequently measure, SA and OA in HMTs, however, when the current definitions for these concepts are so oriented towards humans. To address this issue, this paper provides a reconceptualization of awareness that is agnostic to team composition known as Informational Awareness definitions. It also includes a first look at the Co-Awareness Analytic Framework and a brief example of its use.
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Drury et al. proposed a framework in which machines consider their own option awareness to support human decision makers.
“More recently, Drury et al. [4] proposed a framework in which machines consider their own option awareness to support human decision makers.”
From Explainable AI is Dead, Long Live Explainable AI!: Hypothesis-driven Decision Support using Evaluative AI (2023) · cites this paper as [4]
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Miller, T. (2023) · 2023 ACM Conference on Fairness Accountability and Transparency · doi:10.1145/3593013.3594001 · Cited by 172 · see citing works
Ali, A., Smereka, J. M., Riegner, K. L., Robert, L., & Tilbury, D. M. (2026) · IEEE Access · doi:10.1109/access.2026.3653446 · Cited by 1 · see citing works
- Authors
- Drury, J. L., Klein, G. L., Booker, L., Ryall, K., & Dubrow, S.
- Affiliations
- Mitre (United States) (US)
- McLean,VA,USA
- Venue
- 2022 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)
- Publisher
- IEEE
- Published
- 2022-06-06
- Pages
- 9-15
- OpenAlex
- W4286572097
- Cited by
- 2
- References
- 29
- Citations by year
- 2026: 1 · 2023: 1
- FWCI
- 0.48
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA) (publishedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Social Sciences › Psychology › Social Psychology › Team Dynamics and Performance
- Physical Sciences › Engineering › Control and Systems Engineering › Military Strategy and Technology
- Keywords
- situational awareness, human-machine teams, human-machine teaming, team performance, task dependencies, team composition
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