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Creators/Authors contains: "Bhatti, Shawaiz"

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  1. Workplace research suggests that roughly equal communication between teammates is positively associated with team effectiveness. A distinction between teams in these studies and distributed action teams is the degree of role specialization and context-driven communication which may entail unequal degrees of communication. Yet, distributed action teams may have more equal footing to provide inputs in contexts such as mission planning or briefings. Twenty-two ad hoc teams participated in a simulated ground combat vehicle task in which teams conducted six-missions and briefed before each mission. We used team performance, team situation awareness, team workload, and team resilience as team effectiveness criteria. Balanced degrees of communication in mission briefs were correlated with performance and resilience measures, and largely uncorrelated with situation-awareness and workload measures. The overall amount of communication was also largely uncorrelated with all effectiveness measures. The results suggest that communication balance in mission briefs may help predict effectiveness in action teams. 
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  2. This research examines the relationship between anticipatory pushing of information and trust in human– autonomy teaming in a remotely piloted aircraft system - synthetic task environment. Two participants and one AI teammate emulated by a confederate executed a series of missions under routine and degraded conditions. We addressed the following questions: (1) How do anticipatory pushing of information and trust change from human to human and human to autonomous team members across the two sessions? and (2) How is anticipatory pushing of information associated with the trust placed in a teammate across the two sessions? This study demonstrated two main findings: (1) anticipatory pushing of information and trust differed between human-human and human-AI dyads, and (2) anticipatory pushing of information and trust scores increased among human-human dyads under degraded conditions but decreased in human-AI dyads. 
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