Adversarial Social Epistemology for Assemblies of Humans and Large Language Models
Summary
This paper proposes an adversarial social epistemology framework for analyzing trust, deception, and inference chains in communicative landscapes involving humans and large language models, and outlines mechanisms for auditing trust breaches.
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# Adversarial Social Epistemology for Assemblies of Humans and Large Language Models Source: [https://arxiv.org/abs/2607.07760](https://arxiv.org/abs/2607.07760) [View PDF](https://arxiv.org/pdf/2607.07760) > Abstract:We outline an adversarial social epistemology \(ASE\) for densely interactive communicative landscapes in which public assertions are scaffolded by chains of testimony, inference, institutional certification, and tacit trust\. In such landscapes, agents have incentives and affordances to distort, color, omit, fabricate, or strategically under\-specify information for private, reputational, rhetorical, or material gains\. We argue that these phenomena are not adequately captured by familiar descriptions of epistemic bubbles, echo chambers, or misinformation diffusion\. What requires explanation is how communicative agents exploit the commitments and entitlements that normally make scaffolded assertions trustworthy\. We provide language that delivers the requisite analysis, outline mechanisms that subvert trust in scaffolded public communications, and outline machinery for auditing and redressing trust breaches arising from subverting the auditability of inferential chains, drawing on epistemic networks, enriched with an inferentialist semantics for interpreting assertions\. ## Submission history From: Mihnea Moldoveanu \[[view email](https://arxiv.org/show-email/8909ce20/2607.07760)\] **\[v1\]**Wed, 8 Jul 2026 15:09:49 UTC \(412 KB\)
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