首页|作为人工智能下一个关口的意识研究——从加扎尼加的意识学说切入

作为人工智能下一个关口的意识研究——从加扎尼加的意识学说切入

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随着近年来人工智能(AI)的惊人进步,AI是否具有意识以及如何构建有意识的AI系统越来越受到学界和公众的关注.要回答这类问题,我们仍然需要或者必须从意识理论中去寻找灵感和答案.立足AI意识问题的当前背景,我们考察了加扎尼加在《意识本能:揭秘脑是如何形成心智的》中提出的意识学说.透过脑异常这个窗口,加扎尼加得到了意识现象学的两个重要论断:意识与体验内容不同并且是可以分开的;意识首先是一种感受.为此,他提出了一个关于意识神经机制的模块—层级架构的主张,并用"开水冒泡"隐喻来形象地说明他的意识观.根据这一思路,构建有意识的A1系统需要我们在底层逻辑上辨明"意识"与"智能"的差异和关系,否则,我们就会在AI系统是否有意识以及AI是否会造成对人类的生存性威胁等一系列理论问题上产生困扰.
Consciousness Study as the Next Threshold of Artificial Intelligence from Gazzaniga's Theory of Consciousness
With the amazing advance in Artificial Intelligence(AI)in recent years,the question of whether AI is conscious and how to build a conscious AI has received increasing attention.To answer such questions,we need or must look to theories of consciousness for inspiration and answers.This paper reviews Gazzaniga's theo-ry of consciousness proposed in his book The Consciousness Instinct:Unraveling the Mystery of How the Brain Makes the Mind,grounding in the context of the problem of AI's consciousness.Through the window of the ab-normal brains,which serve as a valuable clue and guide to deduce the neural mechanisms of consciousness,this paper concludes Gazzaniga's two important assertions of such phenomenology:(1)Consciousness and ex-perienced contents are distinct and can be separated;(2)Consciousness is first and foremost a feeling.It is based on these two phenomenological observations that Gazzaniga proposed a modular-layered architecture a-bout the neural mechanism of consciousness,and a metaphor that illustrates the phenomenology of conscious-ness and the modular-layered architecture vividly,that is,the"boiling bubbles".Accordingly,building conscious AI systems requires to identify"consciousness"and"intelligence"in the underlying logic;other-wise,inanimate silicon-based machines will never be able to mimic our consciousness.

李恒威、阮泽楠

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浙江大学哲学学院,浙江杭州 310058

人工智能 加扎尼加 脑异常 模块—层级架构 "开水冒泡"隐喻 意识

国家社会科学基金重大项目国家社会科学基金科技部科技创新2030"脑科学与人类脑研究"重大项目

22&ZD03420BZX0452021ZD0200409

2024

社会科学战线
吉林省社会科学院

社会科学战线

CSTPCDCSSCICHSSCD北大核心
影响因子:0.417
ISSN:0257-0246
年,卷(期):2024.345(3)
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