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Perception of an AI Teammate in an Embodied Control Task Affects Team Performance, Reflected in Human Teammates' Behaviors and Physiological Responses

Authors :
Qin, Yinuo
Lee, Richard T.
Sajda, Paul
Publication Year :
2025

Abstract

The integration of artificial intelligence (AI) into human teams is widely expected to enhance performance and collaboration. However, our study reveals a striking and counterintuitive result: human-AI teams performed worse than human-only teams, especially when task difficulty increased. Using a virtual reality-based sensorimotor task, we observed that the inclusion of an active human-like AI teammate disrupted team dynamics, leading to elevated arousal, reduced engagement, and diminished communication intensity among human participants. These effects persisted even as the human teammates' perception of the AI teammate improved over time. These findings challenge prevailing assumptions about the benefits of AI in team settings and highlight the critical need for human-centered AI design to mitigate adverse physiological and behavioral impacts, ensuring more effective human-AI collaboration.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2501.15332
Document Type :
Working Paper