Do LLM Agents Mirror Socio-Cognitive Effects in Power-Asymmetric Conversations?
Abstract
Power differences shape human communication through well-documented socio-cognitive effects, including language coordination, pronoun usage, authority bias, and harmful compliance.We examine whether large language models (LLMs) exhibit similar behaviors when assigned high-or low-status personas.Using personas from diverse professions, we simulate multi-turn, power-asymmetric dialogues (e.g., principal-teacher, justice-lawyer) and measure (i) linguistic coordination, (ii) pronoun usage, (iii) persuasion success, and (iv) compliance with unsafe requests.Our results show that LLMs show key socio-cognitive effects of power, albeit with nuances and variability, linking simulated interactions to both desirable and unsafe behaviors.1
Fields of Study & Subjects
Action Observation and Synchronization
Language and cultural evolution
AI in Service Interactions
Publication details
- Journal / source
- Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Publisher
- Association for Computational Linguistics
- Pages
- 47676–47701
- Publication date
- 1 January 2026