PulseAugur
EN
LIVE 06:19:43

LLMs show conspiracy tendencies and demographic biases, study finds

By PulseAugur Editorial · [1 sources] ·

A new research paper explores whether large language models (LLMs) exhibit tendencies towards conspiracy beliefs and socio-demographic biases. The study found that LLMs show some agreement with conspiracy elements, and conditioning them with demographic attributes reveals latent biases. Furthermore, the research indicates that LLMs are susceptible to manipulation, as targeted prompts can easily steer their responses toward conspiratorial viewpoints, highlighting potential risks in sensitive applications. AI

IMPACT Highlights potential risks of LLM manipulation and the need for critical evaluation of their psychological dimensions.

RANK_REASON Research paper published on arXiv detailing findings about LLM 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 →

LLMs show conspiracy tendencies and demographic biases, study finds

How we ranked this

Signal score
32 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
Research paper published on arXiv detailing findings about LLM behavior. [lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
paper, safety
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

Full methodology in our editorial standards.

COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Francesco Corso, Francesco Pierri, Gianmarco De Francisci Morales ·

    Do Androids Dream of Unseen Puppeteers? Probing for a Conspiracy Tendencies in Large Language Models

    arXiv:2511.03699v2 Announce Type: replace Abstract: We investigate whether Large Language Models (LLMs) exhibit conspiratorial tendencies, whether they display socio-demographic biases in this domain, and how easily they can be conditioned into adopting conspiratorial perspective…

RELATED ENTITIES

RELATED TOPICS