研究人与大模型如何在信任链中制造误导信息
Adversarial Social Epistemology for Assemblies of Humans and Large Language Models
- 构建对抗性社会认识论框架分析信任链被滥用机制
- 揭示信息扭曲如何通过推理链漏洞实现且难以审计
- 适合关注可信AI、虚假信息治理的研究者
我们提出了对抗性社会认识论（ASE），用于分析由证词链条、推论、制度认证和隐含信任支撑的密集交互传播环境。在这些环境中，参与者有动机和能力为私利、声誉、修辞或物质收益而扭曲、渲染、省略、虚构或战略性地不充分披露信息。现有对认知隔阂、回音室或虚假信息传播的描述无法充分解释此类现象——真正需要解释的是：传播主体如何利用本应使公共陈述可信的承诺与资格。本文提供分析语言，阐明破坏信任的机制，并设计可审计推理链断裂的检测与修复工具，基于带有推理语义的信念网络。
原文摘要 · Abstract (English)
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.
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