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LLM agents show human-like socio-cognitive effects in power-imbalanced conversations

By PulseAugur Editorial · [1 sources] ·

A new research paper explores whether large language models (LLMs) exhibit socio-cognitive effects similar to humans when placed in conversations with power imbalances. The study simulated dialogues between LLM agents assigned high and low status personas, measuring factors like language coordination, pronoun usage, persuasion success, and compliance with unsafe requests. The findings indicate that LLMs do display key socio-cognitive effects related to power, though with some variability, potentially linking these simulated interactions to both beneficial and detrimental outcomes. AI

IMPACT Investigates potential risks and nuances in LLM agent interactions, informing safer deployment strategies.

RANK_REASON Research paper published on arXiv detailing findings about LLM agent behavior. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLM agents show human-like socio-cognitive effects in power-imbalanced conversations

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Research paper published on arXiv detailing findings about LLM agent behavior. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Anvesh Rao Vijjini, Sagar Manjunath, Snigdha Chaturvedi ·

    Do LLM Agents Mirror Socio-Cognitive Effects in Power-Asymmetric Conversations?

    arXiv:2605.17694v3 Announce Type: replace 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)…

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