Adversarial Social Epistemology for Assemblies of Humans and Large Language Models

Jul 11, 2026

A new arXiv paper introduces an adversarial social epistemology (ASE) framework to analyze how agents, including large language models (LLMs), can distort information in complex communicative environments. The authors argue that traditional concepts like echo chambers do not fully explain how trust is subverted in scaffolded public assertions, and they propose mechanisms for auditing and addressing breaches of trust.

Why it matters: This research offers a theoretical basis for understanding and addressing trust and misinformation challenges in human-AI communication systems.

Full story at: arXiv AI/ML ↗