The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
The Perception of Teamwork With an Autonomous Agent Enhances Affect and Performance Outcomes
Abstract
Among groups of humans, the team structure has been argued to be the most effective way for people to organize to accomplish work. Research suggests that humans and autonomous agents can be more effective when working together. However, the drive toward capable autonomous teammates has focused on design characteristics while ignoring the importance of social interactions between teammates. In the present study we created team structure though task interdependence and observed teamwork outcomes in the form of affect, behavior, and performance outcomes. A team structure resulted in improved affect and performance outcomes relative to a non-team structure. However, team structure did not elicit significant behavioral differences. Human partners received higher affect ratings and elicited significantly more communication from the participant than an autonomous partner. These findings suggest that social interactions between humans and autonomous teammates should be an important design consideration. While the current data is promising, team structure alone may not be sufficient to ensure effective teams, so further research should explore the utility of team development interventions between humans and autonomous agents.
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“Based on previous literature, we submit that there are two overarching criteria for autonomous agents to be viewed as a teammate: a degree of interdependence with other team member activities and outcomes (Nass et al., 1996; Walliser et al., 2017), and a degree of agency involving independence of actions and proactivity among autonomous agent members (Lyons et al., 2018; Wynne & Lyons, 2018).”
From Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature (2022) · cites this paper as Walliser et al., 2017
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“Similarly, Walliser et al. (2017) found that outcome interdependence in HATs elicited stronger positive affect and team performance than the lack of outcome interdependence.”
From Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature (2022) · cites this paper as Walliser et al. (2017)
In the citing paper
“human–human teams had higher general positive affect ratings (Walliser et al., 2017)”
From Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature (2022) · cites this paper as Walliser et al., 2017
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Cites
Enhancing the Effectiveness of Work Groups and Teams
Kozlowski, S. W. J., & Ilgen, D. R. (2006) · Psychological Science in the Public Interest · doi:10.1111/j.1529-1006.2006.00030.x · Cited by 2,623
Foundations for an Empirically Determined Scale of Trust in Automated Systems
Jian, J.-Y., Bisantz, A. M., & Drury, C. G. (2000) · International Journal of Cognitive Ergonomics · doi:10.1207/s15327566ijce0401_04 · Cited by 1,799
Merritt, S. M., & Ilgen, D. R. (2008) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872008x288574 · Cited by 527 · cited 1×
“Participants began the study with a short biographical questionnaire followed by the Propensity to Trust Machines questionnaire (Merritt & Ilgen, 2008) and Ten Item Personality Inventory (Gosling, Rentfrow, & Swann, 2003).”
MethodSocial identification effects in group polarization.
Mackie, D. M. (1986) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.50.4.720 · Cited by 280
de Visser, E., & Parasuraman, R. (2011) · Journal of Cognitive Engineering and Decision Making · doi:10.1177/1555343411410160 · Cited by 207 · cited 1×
“For example, human-automation dyads have been found to be more effective at a target recognition task than a human or automated system working alone (de Visser & Parasuraman, 2011).”
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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
Zhang, R., Duan, W., Flathmann, C., McNeese, N., Freeman, G., & Williams, A. (2023) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3610072 · Cited by 134
Panchanadikar, R., & Freeman, G. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790869 · Cited by 3
Metadata
- Authors
- Walliser, J. C., Mead, P. R., & Shaw, T. H.
- Affiliations
- George Mason University
- Venue
- Proceedings of the Human Factors and Ergonomics Society Annual Meeting
- Publisher
- SAGE Publications
- Published
- 2017-09
- Volume
- 61
- Issue
- 1
- Pages
- 231-235
- ISSN
- 1071-1813
- 2169-5067
- Cited by
- 27
- References
- 5
- Language
- en
- Licence
- journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
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