作为认知快捷方式的大型语言模型:超越胡说八道的系统理论重构
1School of Engineering and Computer Science, Bern University of Applied Sciences, Bern, Switzerland.
Frontiers in artificial intelligence
|March 2, 2026
概括
大型语言模型 (LLM) 被重新定义为通用认知快捷方式 (GECOS),作为实用运算符. GECOS减少了沟通的复杂性,使交互连续性和技术语义系统中的意义产生成为可能.
科学领域:
- 技术语义学是一种技术语义学.
- 认知科学 认知科学
- 系统理论 系统理论
背景情况:
- 当前的大型语言模型 (LLM) 话语经常使用缺陷隐喻 (例如",胡说八道"",随机"),专注于对接地,信念或意图的缺乏感知.
- 这些框架掩盖了LLM在创造意义,构想和沟通过程中的实际实用性.
- 需要一个非人形的框架来理解在人机交互中LLM的功能.
研究的目的:
- 重构大型语言模型 (LLM) 不是作为具有代理或理解的实体,而是作为技术语义组合中的功能操作员.
- 开发一个理论模型,GECOS (通用认知快捷方式),以减少沟通复杂性和交互连续性来解释LLM的实用性.
- 将焦点从关于LLM"理解"的存在论辩转移到它们在分布式意义制造中的操作作用.
主要方法:
- 整合了卢曼尼的系统理论,德鲁兹的本体学和胡塞尔的现象学的概念.
- 概念分析作为功能比较合成方法的应用.
- 对人与LLM互动的分析,而不是对LLM赋予人形特质,如代理,信念或理解.
主要成果:
- 简称GECOS的LLM通过接近"二次期望"来降低沟通复杂性,促进交互连续性.
- GECOS框架通过程序的可信性和连贯性来解释LLM的实用性,帮助用户通过Luhmann的应急公式来导航不确定性.
- 通过生成可连接的文本,LLM可以实现可行的延续,独立于真实性或故意性.
结论:
- 在复杂的社会技术环境中,GECOS框架提供了一个非人形模型来理解LLMs作为务实操作者.
- 这种重构将注意力从LLM的"理解"转移到它们在分布式意义制造和通信中的操作作用.
- 潜在的风险包括过度依赖,情绪投射和规范平整,当连接性取代理由时.
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