为什么大型语言模型不能拥有意识:一个整合的信息理论视角
Dong Ah Shin1, Pyung Goo Cho2, Gyu Yeul Ji3
1Department of Neurosurgery, Spine and Spinal Cord Institute, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.
Journal of Yeungnam medical science
|December 2, 2025
概括
根据综合信息理论 (IIT),大型语言模型 (LLM) 不表现出意识. 尽管语言流利,但LLM缺乏必要的集成和持续状态,这是有意识经验所需的.
科学领域:
- 人工智能的人工智能
- 认知科学 认知科学
- 神经科学是一个神经科学.
背景情况:
- 关于大语言模型 (LLM) 意识的辩论正在进行中.
- 综合信息理论 (IIT) 为意识提供了量化衡量标准.
研究的目的:
- 通过使用 IIT 原则来评估LLM意识.
- 研究LLM架构的因果整合,时间持久性和不可缩小性.
主要方法:
- 应用IIT到基于变压器的LLMs.
- 在GPT-2上进行了废除实验,去除了注意力头.
- 使用困惑性变化作为综合信息的代理.
主要成果:
- LLM 符合 IIT 的差异化标准,但不符合整合,因果关闭或时间持久性.
- 废弃性研究显示单个注意力头的影响很小,这表明了建筑的分解性.
- 根据哲学论点,LLM表现出语法操纵而不是语义理解.
结论:
- 当前的LLM不符合IIT对意识的要求.
- 法律法规模拟智能,但缺乏综合信息和有意识的经验.
- 在语言能力和真正的意识之间存在着明确的区别.
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