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Team Structure and Team Building Improve Human–Machine Teaming With Autonomous Agents
Abstract
Research suggests that humans and autonomous agents can be more effective when working together as a combined unit rather than as individual entities. However, most research has focused on autonomous agent design characteristics while ignoring the importance of social interactions and team dynamics. Two experiments examined how the perception of teamwork among human–human and human–autonomous agents and the application of team building interventions could enhance teamwork outcomes. Participants collaborated with either a human or an autonomous agent. In the first experiment, it was revealed that manipulating team structure by considering your human and autonomous partner as a teammate rather than a tool can increase affect and behavior, but does not benefit performance. In the second experiment, participants completed goal setting and role clarification (team building) with their teammate prior to task performance. Team building interventions led to significant improvements for all teamwork outcomes, including performance. Across both studies, participants communicated more substantially with human partners than they did with autonomous partners. Taken together, these findings suggest that social interactions between humans and autonomous teammates should be an important design consideration and that particular attention should be given to team building interventions to improve affect, behavior, and performance.
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“Interdependence is relatively straightforward to identify, as it can be built into the task design and outcome distribution (e.g., McNeese et al., 2018, Nass et al., 1996; Walliser et al., 2019, 2019).”
From Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature (2022) · cites this paper as Walliser et al., 2019, 2019
In the citing paper
“(I) Training humans with agent autonomy produced consistently positive results including increased mental model similarity, trust, and lower uncertainty.”
From Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature (2022) · cites this paper as Walliser et al. (2019)
In the citing paper
“by increasing the extent to which both humans and autonomous agents necessarily needed to work together to complete the task, there was a subsequent increase in participant positive affect and team performance (Walliser et al., 2019, 2019).”
From Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature (2022) · cites this paper as Walliser et al., 2019
In the citing paper
“by increasing the extent to which both humans and autonomous agents necessarily needed to work together to complete the task, there was a subsequent increase in participant positive affect and team performance (Walliser et al., 2019, 2019).”
From Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature (2022) · cites this paper as Walliser et al., 2019
In the citing paper
“Walliser et al. (2019) found that goal setting and role clarification prior to performing the task was superior to playing a “team-building” (cooperative) game.”
From Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature (2022) · cites this paper as Walliser et al., 2019
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“Research conducted under the CASA paradigm has demonstrated that the presence of interdependence and identity even on a simple desktop computer is sufficient to elicit knowledge structures related to team social interactions (e.g., Epley, Waytz, & Cacioppo, 2007; Nass & Moon, 2000).”
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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
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Self-citationMeasurement of trust in automation: A narrative review and reference guide
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Metadata
- Authors
- Walliser, J. C., de Visser, E. J., Wiese, E., & Shaw, T. H.
- Affiliations
- Air Force Nuclear Weapons Center, USA
- George Mason University, USA and United States Air Force Academy, USA
- George Mason University, USA
- ORCID
- de Visser, Ewart J.
- Venue
- Journal of Cognitive Engineering and Decision Making
- Publisher
- SAGE Publications
- Published
- 2019-08-09
- Volume
- 13
- Issue
- 4
- Pages
- 258-278
- ISSN
- 1555-3434
- Cited by
- 93
- References
- 19
- Language
- en
- Funders
- Air Force Office of Scientific Research (FA9550-16-1-0023)
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