发表机构
Fondazione Bruno Kessler（布鲁诺·凯斯勒基金会）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究大语言模型输出致“认知症”现象，挑战其解释框架。借鉴相关哲学，将大语言模型视为技术符号机器，指出“认知症”是“认知分裂症”后果，强调相关单元是整个实践，为新设计方案奠定基础。
AI 中文摘要
夸特罗基奥基及其同事警告说，大语言模型流畅的输出可能会让语言上的合理性取代认知评估，产生他们所称的“认知症”：即一种在未进行通常能保证判断的实践的情况下却拥有知识的体验。本文认同这一诊断，但对其解释框架提出挑战，该框架将具身的、处于社会情境中的人类认知者与孤立的生成模型进行比较，从而将认知合法性定位在自主主体内部的能力上。借鉴卡洛·西尼关于实践、写作、符号和技术的哲学，我们反而提议将大语言模型理解为一种“技术符号机器”，它通过从人类写作的沉淀档案中生成合理的语言配置，使书面符号学的一个阶段自动化。从这个角度来看，“认知症”是我们所称的“认知分裂症”这一更广泛现象的一个后果：即作为语言上完成的表达的符号与作为社会嵌入的解释、证据、批评、验证和责任回路中的时刻的符号之间的社会技术分裂。这种分裂通过“似真闭合”得到加强，通过这种方式，一个合理的延续以认知结果的确定性呈现出来，同时也受到算法权威和认知自我误认的影响。因此，相关单元不是单独的模型，而是整个实践，在这个实践中，生成的铭文被提示、解释、验证、质疑、使用并产生后果。这种重新构建保留了语言生产与负责任的理解之间的区别，同时为一个以可检查的谱系、可争议性、分布式责任、认知能动性以及对人类与人工智能混合实践的评估为中心的设计方案奠定了基础。
英文摘要
Quattrociocchi and colleagues warn that the fluent outputs of large language models may allow linguistic plausibility to substitute for epistemic evaluation, producing the condition they call *Epistemia*: the experience of possessing knowledge without undertaking the practices through which judgment would ordinarily be warranted. This article accepts that diagnosis but challenges its explanatory framework, which compares an embodied, socially situated human knower with an isolated generative model thereby locating epistemic legitimacy in capacities internal to autonomous agents. Drawing on Carlo Sini's philosophy of practices, writing, signs, and technics, we propose instead to understand a large language model (LLM) as a *techno-semiotic machine* that automates a phase of written semiosis by producing plausible linguistic configurations from the sedimented archive of human writing. From this perspective, *Epistemia* is one consequence of a broader phenomenon that we call *epistemic schizologia*: the socio-technical cleavage between signs as linguistically accomplished expressions and signs as moments within socially embedded circuits of interpretation, evidence, criticism, verification, and responsibility. This cleavage is reinforced by *eikotic closure*, through which a plausible continuation is presented with the finality of an epistemic result, and by algorithmic authority and epistemic self-misrecognition. The relevant unit is therefore not the model alone but the complete practice in which generated inscriptions are prompted, interpreted, verified, contested, used, and made consequential. This reframing preserves the distinction between linguistic production and responsible understanding while grounding a design programme centred on inspectable genealogy, contestability, distributed responsibility, epistemic agency, and the evaluation of hybrid human--AIpractices.
