The Hierarchical Correspondence View of Levels: A Case Study in Cognitive Science

IF 4.2 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Luke Kersten
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引用次数: 0

Abstract

There is a general conception of levels in philosophy which says that the world is arrayed into a hierarchy of levels and that there are different modes of analysis that correspond to each level of this hierarchy, what can be labelled the ‘Hierarchical Correspondence View of Levels” (or HCL). The trouble is that despite its considerable lineage and general status in philosophy of science and metaphysics the HCL has largely escaped analysis in specific domains of inquiry. The goal of this paper is to take up a recent call to domain-specificity by examining the role of the HCL in cognitive science. I argue that the HCL is, in fact, a conception of levels that has been employed in cognitive science and that cognitive scientists should avoid its use where possible. The argument is that the HCL is problematic when applied to cognitive science specifically because it fails to distinguish two important kinds of shifts used when analysing information processing systems: shifts in grain and shifts in analysis. I conclude by proposing a revised version of the HCL which accommodates the distinction.

层次对应观:认知科学案例研究
哲学中有一种关于层次的一般概念,即世界是由一个个层次组成的,而每一个层次都对应着不同的分析模式,这就是 "层次对应观"(或 HCL)。问题在于,尽管 "层次对应观 "在科学哲学和形而上学中具有相当的渊源和普遍地位,但它在具体的研究领域却基本上没有得到分析。本文的目的是通过研究 HCL 在认知科学中的作用,响应最近对特定领域的呼吁。我认为,HCL 实际上是认知科学中使用的一种水平概念,认知科学家应尽可能避免使用它。我的论点是,HCL 在认知科学中的应用是有问题的,特别是因为它未能区分在分析信息处理系统时使用的两种重要的转变:粒度的转变和分析的转变。最后,我提出了一个修订版的 HCL,以适应这种区分。
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来源期刊
Minds and Machines
Minds and Machines 工程技术-计算机:人工智能
CiteScore
12.60
自引率
2.70%
发文量
30
审稿时长
>12 weeks
期刊介绍: Minds and Machines, affiliated with the Society for Machines and Mentality, serves as a platform for fostering critical dialogue between the AI and philosophical communities. With a focus on problems of shared interest, the journal actively encourages discussions on the philosophical aspects of computer science. Offering a global forum, Minds and Machines provides a space to debate and explore important and contentious issues within its editorial focus. The journal presents special editions dedicated to specific topics, invites critical responses to previously published works, and features review essays addressing current problem scenarios. By facilitating a diverse range of perspectives, Minds and Machines encourages a reevaluation of the status quo and the development of new insights. Through this collaborative approach, the journal aims to bridge the gap between AI and philosophy, fostering a tradition of critique and ensuring these fields remain connected and relevant.
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