人工智能思维的三个框架
1Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge, United Kingdom.
Frontiers in psychology
|February 20, 2026
概括
大型语言模型 (LLM) 促使用户将思维归因于AI. 这篇论文分析了人工智能思维的三个框架,提出了"最小认知代理人"对分级信念和欲望归因的观点.
科学领域:
- 人工智能的人工智能
- 认知科学 认知科学
- 思想的哲学 思想的哲学
背景情况:
- 大型语言模型 (LLM) 的快速进步导致公众和用户对人工智能的认知度增加.
- 现有的理解人工智能思维的框架包括"无意识的机器"和"纯粹的角色扮演"观点.
- 这些框架在解释用户属性和AI认知的性质方面面临着挑战.
研究的目的:
- 提供对人工智能思维特征的结构化分析.
- 批判性地评估现有的框架,以了解AI认知.
- 提出一种新的框架,用于将心理状态归因于LLMs.
主要方法:
- 使用马尔的分析水平,分析架构揭穿论据的分析.
- 对人工智能交互的"纯粹角色扮演"类比的评估.
- 开发一个"最小的认知代理"框架.
主要成果:
- 建筑解释并不能完全否定民间心理学解释的需要,区分实施敏感和冷漠的概念.
- "简单的角色扮演"观点在心理上是不稳定的,在理论上是不完整的,对于人类形态的人工智能.
- 在"最小的认知代理人"框架下,LLM可能会保证有限的,分级的信念和欲望状态的归属.
结论:
- 必须超越二进制的信念观念,转向多维的,连续的模型.
- 这种方法可以更好地捕捉有关AI的当前解释实践.
- 它有助于保持人类,LLM和更简单的系统认知之间的区别.
关键词:
人类形象主义 (anthropomorphism) 是一种人类形象主义.民族心理学 民族心理学人与人工智能之间的关系大型语言模型.人工智能的哲学是AI的哲学.社会人工智能社会AI理论理论理论的理论是什么更多相关视频
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