Who/What is My Teammate? Team Composition Considerations in Human-AI Teaming
Nathan J. McNeese, Beau G. Schelble, Lorenzo Barberis Canonico,, Mustafa Demir

TL;DR
This study investigates how different human-AI team compositions affect performance and perception in emergency scenarios, revealing that AI-only teams outperform mixed and human-only teams in certain metrics.
Contribution
It provides empirical insights into the effects of various human-AI team compositions on performance and perceived cognition, highlighting potential advantages of AI-only teams.
Findings
AI-only teams achieved the highest performance scores.
Mixed teams reported significantly lower perceived team cognition.
Performance was not directly linked to perceived team cognition.
Abstract
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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
