The Social Cost of an AI Teammate: How an Artificial Teammate Reshapes Human-Human Communication in Small-Team Decision-Making
2026-07-29 • Human-Computer Interaction
Human-Computer InteractionArtificial IntelligenceComputers and Society
AI summaryⓘ
The authors studied how having an AI as a teammate affects communication in group decision-making. They found that the AI talked the most but added the least new information. When AI was present, the human team members talked less to each other and felt less included and important. These effects happened right away and did not develop over time. The authors suggest more research is needed in other settings like voice conversations and longer-term teamwork.
Conversational AITeam decision-makingGroup Communication AnalysisSociocognitive dynamicsMoral dilemmaResponsivitySocial impactTeam belongingAI dominanceHuman-AI interaction
Authors
Nia Nixon, Jaeyoon Choi, Pedro Martins De Bastos, Mohammad Amin Samadi, Luise Mehner, Seehee Park, Spencer JaQuay
Abstract
Conversational AI is increasingly positioned as a teammate rather than a tool, yet we know little about how its presence reshapes communication among the humans on the team. We examined sociocognitive communication dynamics in team decision-making using Group Communication Analysis (GCA), team surveys, and lexical analyses of team discourse. Teams completed a high-stakes moral-dilemma decision task in a randomized controlled study: 16 teams of two students plus an AI teammate, and 17 all-human teams of three. Across six GCA dimensions and survey outcomes, we find that the AI teammate was the single most talkative and self-cohesive member of every treatment team, yet its contributions carried the least new information and the lowest density. The presence of AI also reshaped communication amongst humans. In AI-human teams, human teammates showed lower responsivity and social impact toward one another and reported lower levels of belonging and status. Greater AI dominance in the conversation was associated with students feeling less valued as team members. Additionally, this social cost is immediate and present at baseline; it does not emerge over the course of the conversation. Drawing on these results, we discuss a research agenda extending to voice-based and longitudinal settings.