Who/What is My Teammate? Team Composition Considerations in Human-AI Teaming
This addresses the problem of optimizing team performance and dynamics for practitioners in human-AI collaboration, though it is incremental as it applies existing concepts to a new context.
The paper investigated how team composition (human-only, mixed human-AI, AI-only) affects performance and perceived cognition in a simulated emergency response scenario, finding that AI-only teams achieved the highest performance while human-only teams had the highest perceived team cognition, with mixed teams showing 58% lower perceived cognition.
There are many unknowns regarding the characteristics and dynamics of human-AI teams, including a lack of understanding of how certain human-human teaming concepts may or may not apply to human-AI teams and how this composition affects team performance. This paper outlines an experimental research study that investigates essential aspects of human-AI teaming such as team performance, team situation awareness, and perceived team cognition in various mixed composition teams (human-only, human-human-AI, human-AI-AI, and AI-only) through a simulated emergency response management scenario. Results indicate dichotomous outcomes regarding perceived team cognition and performance metrics, as perceived team cognition was not predictive of performance. Performance metrics like team situational awareness and team score showed that teams composed of all human participants performed at a lower level than mixed human-AI teams, with the AI-only teams attaining the highest performance. Perceived team cognition was highest in human-only teams, with mixed composition teams reporting perceived team cognition 58% below the all-human teams. These results inform future mixed teams of the potential performance gains in utilizing mixed teams' over human-only teams in certain applications, while also highlighting mixed teams' adverse effects on perceived team cognition.