TY - JOUR
T1 - Team Situation Awareness and Conflict
T2 - A Study of Human–Machine Teaming
AU - McNeese, Nathan J.
AU - Demir, Mustafa
AU - Cooke, Nancy J.
AU - She, Manrong
N1 - Funding Information:
This research was partially supported by ONR Award N000141110844 (Program Managers: Marc Steinberg, Paul Bello). The authors acknowledge Steven M. Shope from Sandia Research Corporation, who helped develop the synthetic environment.
Publisher Copyright:
© 2021, Human Factors and Ergonomics Society.
PY - 2021/9
Y1 - 2021/9
N2 - This article focuses on two fundamental human–human teamwork behaviors and seeks to understand them better in human–machine teams. Specifically, team situation awareness (TSA) and team conflict are examined in human–machine teams. There is a significant need to identify how TSA and team conflict occur during human–machine teaming, in addition to how they impact each other. In this work, we present an experiment aimed at understanding TSA and team conflict in the context of human–machine teaming in a remotely piloted aircraft system (RPAS). Three conditions were tested: (1) control: teams consisted of all humans; (2) synthetic: teams consisted of the pilot role being occupied by a computational agent based on ACT-R architecture that employed AI capabilities, with all other team roles being humans; and (3) experimenter: an experimenter playing the role of the pilot as a highly effective computational agent, with the other roles being humans. The results indicate that TSA improved over time in synthetic teams, improved and then stabilized over time in experimenter teams, and did not improve in control teams. In addition, results show that control teams had the most team conflict. Finally, in the control condition, team conflict negatively impacts TSA.
AB - This article focuses on two fundamental human–human teamwork behaviors and seeks to understand them better in human–machine teams. Specifically, team situation awareness (TSA) and team conflict are examined in human–machine teams. There is a significant need to identify how TSA and team conflict occur during human–machine teaming, in addition to how they impact each other. In this work, we present an experiment aimed at understanding TSA and team conflict in the context of human–machine teaming in a remotely piloted aircraft system (RPAS). Three conditions were tested: (1) control: teams consisted of all humans; (2) synthetic: teams consisted of the pilot role being occupied by a computational agent based on ACT-R architecture that employed AI capabilities, with all other team roles being humans; and (3) experimenter: an experimenter playing the role of the pilot as a highly effective computational agent, with the other roles being humans. The results indicate that TSA improved over time in synthetic teams, improved and then stabilized over time in experimenter teams, and did not improve in control teams. In addition, results show that control teams had the most team conflict. Finally, in the control condition, team conflict negatively impacts TSA.
KW - human–machine teaming
KW - team conflict
KW - team effectiveness
KW - team situational awareness
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U2 - 10.1177/15553434211017354
DO - 10.1177/15553434211017354
M3 - Article
AN - SCOPUS:85106438466
SN - 1555-3434
VL - 15
SP - 83
EP - 96
JO - Journal of Cognitive Engineering and Decision Making
JF - Journal of Cognitive Engineering and Decision Making
IS - 2-3
ER -