New framework analyzes LLM-human communication and trust breaches

Researchers have introduced a framework called Adversarial Social Epistemology (ASE) to analyze complex communication environments involving both humans and large language models. This framework addresses how agents can manipulate information for personal gain within systems that rely on testimony, inference, and certification. The paper proposes language and mechanisms to identify and counteract breaches of trust in these scaffolded communication landscapes, particularly by auditing inferential chains. AI

IMPACT Introduces a framework for understanding and mitigating information manipulation in human-AI communication systems.

RANK_REASON The cluster contains a research paper published on arXiv detailing a new theoretical framework. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• Adversarial Social Epistemology
• arXiv
• Hugging Face
• large-language models

• paper
• safety

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