AI's Social Forcefield: Reshaping Distributed Cognition in Human-AI Teams
This addresses the challenge of responsible AI integration in team settings, highlighting a double-edged impact on collaboration, but it is incremental as it builds on existing distributed cognition frameworks.
The paper tackles the problem of AI's influence on human-AI team collaboration by showing that exposure to AI-generated language reshapes how people speak, think, attend, and relate, revealing AI as an implicit social forcefield that can erode epistemic diversity.
AI is not only a neutral tool in team settings; it actively reshapes the social and cognitive fabric of collaboration. We advance a unified framework of alignment in distributed cognition in human-AI teams -- a process through which linguistic, cognitive, and social coordination emerge as human and AI agents co-construct a shared representational space. Across two studies, we show that exposure to AI-generated language shapes not only how people speak, but also how they think, what they attend to, and how they relate to each other. Together, these findings reveal how AI participation reorganizes the distributed cognitive architecture of teams: AI systems function as implicit social forcefields. Our findings highlight the double-edged impact of AI: the same mechanisms that enable efficient collaboration can also erode epistemic diversity and undermine natural alignment processes. We argue for rethinking AI in teams as a socially influential actor and call for new design paradigms that foreground transparency, controllability, and group-level dynamics to foster responsible, productive human-AI collaboration.