Mind Your Manners: The Dynamics of Politeness in Human-AI vs. Human-Human Interactions
Teddy Lazebnik, Lior Zalmanson, Osnat Mokryn
摘要
The rapid integration of artificial intelligence (AI) into communication systems has significantly altered how users interact with digital tools and collaborate with AI agents. This study investigates the dynamics of politeness in human-AI interactions through a controlled experiment with 1,684 participants, each completing sequential text-based tasks with a conversational AI system. Participants were randomly assigned to one of several conditions that varied in the AI's visual identity (no icon, robot icon, or human face), allowing us to examine the role of perceived anthropomorphism through a minimal visual cue. Politeness was measured using linguistic markers and analyzed using statistical models that account for task sequence and individual differences. Our findings show that politeness toward AI declines over time, with a temporary increase at the start of a second task. Compared to human-human interactions in a benchmark dataset, politeness in human-AI interactions eroded more quickly. Younger participants were less polite overall, and although frequent AI users also appeared less polite descriptively, adjusted models showed a small positive association with daily AI use. Anthropomorphic visual cues, especially human-like avatars, led to more sustained polite behavior. These results offer insight into how users adapt social norms in AI-mediated collaboration and suggest design strategies for fostering respectful and effective human-AI communication.
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