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This paper draws on lessons from social-science accounts of human-human collaboration and argues that human-AI systems amplify these dynamics, introducing new asymmetries that make reasoning about uncertainty harder and introduce new coordination challenges.
Evaluating three frontier models across six games in homogeneous and heterogeneous groups over 10 rounds, it is found that different models interpret announcements incompatibly, some as binding commitments and others as cheap talk, producing payoff gaps that emerge in Round~0 and persist across all 10 rounds.
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