表征生成中的预设问题
The Presupposition Problem in Representation Genesis
AI总结:
本文探讨了大语言模型在未经历表征生成过渡时的认知能力问题,指出现有哲学框架存在预设结构导致解释延迟,并提出表征回归概念。
摘要:
大型语言模型是首个在未明确经历表征生成过渡的情况下实现高认知性能的系统:从非表征物理系统到状态引导行为的敏感内容系统。先前认知系统已在此过渡前完成,而心灵哲学将其视为背景条件而非解释目标。LLMs提供了一个不明显涉及此过渡的案例,使生成问题变得紧迫:若未发生生成,哪些认知能力受影响?本文指出,现有哲学框架在解释生成问题时存在预设结构,导致解释延迟。本文提出表征回归概念,并为避免此模式的理论建立两个最小充分条件。
英文摘要:
Large language models are the first systems to achieve high cognitive performance without clearly undergoing representation genesis: the transition from a non-representing physical system to one whose states guide behavior in a content-sensitive way. Prior cognitive systems had already made this transition before we could examine it, and philosophy of mind treated genesis as a background condition rather than an explanatory target. LLMs provide a case that does not clearly involve this transition, making the genesis question newly urgent: if genesis did not occur, which cognitive capacities are affected, and why? We currently lack the conceptual resources to answer this. The reason, this paper argues, is structural. Major frameworks in philosophy of mind, including the Language of Thought hypothesis, teleosemantics, predictive processing, enactivism, and genetic phenomenology, share a common feature when applied to the genesis question: at some explanatory step, each deploys concepts whose explanatory purchase depends on the system already being organized as a representer. This pattern, which we call the Representation Presupposition structure, generates systematic explanatory deferral. Attempts to explain the first acquisition of content-manipulable representation within the existing categorical vocabulary import resources from the representational side of the transition itself. We call this the Representation Regress. The paper offers a conceptual diagnosis rather than a new theory, establishing the structure of the problem and deriving two minimum adequacy conditions for any account that avoids this pattern. LLMs make the absence of such a theory consequential rather than merely theoretical.
机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。