Ai conversation mimics politeness but lacks true cooperation
Talking Past the Machine: Morality, Politeness, and Alignment in Human-AI Dialogue
Computation and LanguageArtificial Intelligence
Summary
Conversations with AI like ChatGPT seem polite and moral on the surface but don’t truly cooperate like humans do. The authors found AI responses follow social cues without real give-and-take or adjustment during conversation. In fact, some polite behaviors that help human cooperation seem to have the opposite effect with AI. This means AI dialogue might feel friendly but doesn’t fully engage in human-style back-and-forth communication.
What this means in practice
- •For conversational ai developers: Identify which dialogue features improve real cooperation rather than just surface politeness in human-AI chats to design more effective AI systems.
- •For customer support teams: Adjust AI assistants to create dialogues that better allow customers to influence the conversation, boosting alignment and satisfaction.
Authors
Marina Mitiaeva, Lu Xiao
Abstract
Conversational AI systems produce fluent, socially appropriate responses, yet whether they participate in cooperative communication or merely simulate its surface forms remains unclear - a question central to how these systems are evaluated, trusted, and designed. This study investigates how morality, politeness, and alignment - three dimensions central to cooperative dialogue - function in human-AI interaction compared to human-human conversation. We analyze 15,881 human-ChatGPT and 10,784 human-human multi-turn dialogues, using mixed-effects models to identify which features predict turn-to-turn alignment. We observe a consistent dissociation: AI produces the surface features of cooperative communication without the underlying social architecture. Moral output appears preconfigured rather than negotiated; warmth is generated without face sensitivity; linguistic convergence declines persistently. Most strikingly, the cooperative mechanisms themselves reverse direction: hedging and softening associated with greater accommodation between humans are associated with reduced alignment when produced by AI, and purity framing associated with human divergence coincides with users converging toward the AI. Agency - giving users room to shape the exchange - is the most consistent predictor of alignment across both interaction types, while lower moral assertiveness in more recent models is not accompanied by better cooperation. Together these patterns suggest that AI reproduces the surface of cooperation without the mutual adaptation that grounds it between humans - and, more surprisingly, that mechanisms sustaining human accommodation can run in reverse with AI, suggesting a turn-level view may be insufficient for interaction-level success.