附着与隧通——心 智 的 工 作 模 式

蔡恒进1; 蔡天琪2

附着与隧通——心智的工作模式

引用本文：蔡恒进1，蔡天琪2.附着与隧通——心智的工作模式[J].湖南大学学报社会科学版,2021,(4):122-128

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作者	单位
蔡恒进1，蔡天琪2	（1.武汉大学计算机学院，湖北武汉 430072 2.卓尔智联研究院，湖北武汉 432200）

中文摘要:深度学习框架加速了人工智能技术的发展，越来越多的人工智能系统在专业领域超越人类，但沿此路径能否指引机器模拟出类人智能仍然没有定论。强计算主义的观点主张意识和智能可以被物理还原，甚至可以忽略意识。哥德尔等学者则倾向于机器无法模拟或超越人类。文章提出认知坎陷（意识片段）的“附着”与“隧通”这一对范畴，从新的视角探讨心智的工作模式。认知坎陷具有超越时空和流变的特性，在某时某地某景可以“附着”在某个具体对象之上。认知坎陷之间可以通过“隧通”链接成一个网络。“自我”作为最原初和最重要的认知坎陷，是人类意识与智能的发端。智能的作用之一是在情景改变时将“自我”“附着”到更合适的对象上。

中文关键词:意识强人工智能图灵机认知坎陷

Bandwagoning and Tunneling: The Working Mode of Mind

Abstract:Deep learning framework accelerates the development of Artificial Intelligence. More and more AI systems have surpassed human beings in professional fields, but whether this path can lead machines to simulate human like intelligence remains unclear. Strong Computationalism asserts that consciousness and intelligence can be physically reduced and that consciousness can even be eliminated, while other scholars like Godel tend to believe that machines cannot emulate or surpass humans. This paper proposes a pair of categories of bandwagoning and tunneling of cognitive attractors or consciousness fragments to explore the working mode of the mind from a new perspective. Cognitive attractors or consciousness fragments are beyond time and space, but at a certain point of time and space, a cognitive attractor can bandwagon to a specific object. Cognitive attractors can be tunneled with each other into a network. As the most primitive and important cognitive attractor, Self is the origin of human consciousness and intelligence. One function of intelligence is to tunnel Self to appropriate objects when situations change.

keywords:consciousness strong AI Turing machine cognitive attractor

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