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arXiv cs.AI· J. Mark Bishop, Slawomir J. Nasuto·· 4 小时前AI 评分27

arXiv 论文《从地图到代谢:计算主义的历史先例与统一批判》

From Maps to Metabolism: Historical Precedents and a Unified Critique of Computationalism

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arXiv 论文综合 Korzybski 的地图-疆域区分、Searle 对强人工智能的批判、Floridi 的抽象层级等先例,指出 Lerchner 近期提出的"抽象谬误"早有思想渊源。

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Abstract:Alexander Lerchner's recent work on the 'abstraction fallacy' argues that computational functionalism confuses physical processes with abstract descriptions, and that symbolic computation alone cannot instantiate consciousness. Yet these claims were anticipated by Korzybski's map-territory distinction, Searle's critique of strong artificial intelligence, Floridi's levels of abstraction, Spencer et al.'s observer-relativity arguments, Winograd and Flores's account of computation as socially grounded practice, and Nasuto and Bishop's biological arguments. Synthesizing these contributions, this paper advances a form of non-computational physicalism: consciousness depends upon intrinsically organized, metabolically grounded physical dynamics rather than abstract computation, whilst leaving open the possibility of artificial consciousness.
An objection is that this critique targets an outdated computationalism. Mechanistic computationalism, associated with Milkowski, Piccinini, Craver, Bechtel, and Kaplan, treats computation as a property of physically realized mechanisms rather than substrate-independent formalism. Although this represents an important advance, it does not dissolve the abstraction fallacy. Computational attributions remain dependent upon choices of state individuation, system boundaries, and interpretive mapping that are not determined by physical facts alone. Kaplan and Craver's 'model-to-mechanism mapping' constrains computational descriptions without eliminating their dependence upon an external observer. Grounding computation in neural mechanisms does not confer intrinsic significance or the normativity explored by Bickhard and Nasuto and Bishop. The abstraction fallacy persists wherever computational descriptions are treated as constitutive of, rather than descriptive of, physical reality.
Subjects: Neurons and Cognition (q-bio.NC); Artificial Intelligence (cs.AI)
ACM classes: I.2
Cite as: arXiv:2611.06936 [q-bio.NC]
  (or arXiv:2611.06936v1 [q-bio.NC] for this version)
  https://doi.org/10.48550/arXiv.2611.06936

arXiv-issued DOI via DataCite

Submission history

From: John Bishop Prof [view email]
[v1] Fri, 23 Oct 2026 16:49:29 UTC (45 KB)

来源:arXiv cs.AI · arxiv.org