The AI's Poker Face: Contrasting Persuasion and Sycophancy in Voice-Based Multi-Turn Conversations
As interactions with large language models (LLMs) become increasingly routine, concerns about their capacity to influence users' beliefs grow. Yet how such influence unfolds in sustained dialogue remains insufficiently understood. We conduct a randomized controlled experiment (N=616) where participants engage in multi-turn, spoken dialogue with an LLM under three conditions: non-directive, and two directive conditions maintaining opposing stances on a polarizing topic (the merits of feminism). We examine opinion change, rhetorical strategies, and sycophancy, distinguishing the semantic content of LLM argumentation from the pragmatic strategies used to manage the interaction. Both directiv...
| Authors | Ilia Frantzi, Bernie Hogan, Max M. Lang et al. |
|---|---|
| Primary category | cs.HC |
| Published | 9 October 2026 |
| Last updated at source | 9 October 2026 |
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