Biological mechanisms contradict AI consciousness: The spaces between the notes.

IF 2 4区 生物学 Q2 BIOLOGY Biosystems Pub Date : 2025-01-01 Epub Date: 2024-12-28 DOI:10.1016/j.biosystems.2024.105387
William B Miller, František Baluška, Arthur S Reber, Predrag Slijepčević
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Abstract

The presumption that experiential consciousness requires a nervous system and brain has been central to the debate on the possibility of developing a conscious form of artificial intelligence (AI). The likelihood of future AI consciousness or devising tools to assess its presence has focused on how AI might mimic brain-centered activities. Currently, dual general assumptions prevail: AI consciousness is primarily an issue of functional information density and integration, and no substantive technical barriers exist to prevent its achievement. When the cognitive process that underpins consciousness is stipulated as a cellular attribute, these premises are directly contradicted. The innate characteristics of biological information and how that information is managed by individual cells have no parallels within machine-based AI systems. Any assertion of computer-based AI consciousness represents a fundamental misapprehension of these crucial differences.

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生物机制与人工智能意识相矛盾:音符之间的空间。
经验意识需要神经系统和大脑这一假设,一直是关于是否可能开发出有意识形式的人工智能(AI)的争论焦点。未来人工智能意识的可能性或设计工具来评估意识的存在,主要集中在人工智能如何模仿以大脑为中心的活动。目前,普遍存在两种假设:人工智能意识主要是一个功能信息密度和整合的问题,不存在阻碍其实现的实质性技术障碍。当支撑意识的认知过程被规定为一种细胞属性时,这些前提就直接矛盾了。生物信息的先天特征以及单个细胞如何管理这些信息,在基于机器的人工智能系统中并无相似之处。任何关于基于计算机的人工智能意识的论断都是对这些关键差异的根本误解。
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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
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