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Intrinsic Computational Functionalism and Simulated Consciousness

arXiv 2606.15348 ↗First posted 13 Jun 2026q-bio.NC cs.AIcited by 0

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Abstract (arXiv)

A common objection to artificial or simulated consciousness is that a simulated brain is no more conscious than simulated water is wet. We address this from the perspective of Intrinsic Computational Functionalism (ICF): if consciousness is computationally constituted, it depends not on externally imposed descriptions but on the computational structures a system physically realizes in virtue of its own causal-dynamical organization. In previous work we developed Canonical Functionalism as a mathematically precise special case of this anti-interpretivist program, identifying functional states by their complete future input-output roles under a fixed interface. Here we argue that this input-output construction, though important, is incomplete: as a behavioral boundary case of ICF, it makes lookup tables and unfolded systems that preserve the same boundary behavior canonically equivalent. A consciousness-relevant canonical representation must instead include internal mechanisms, interventions, and joint readouts belonging to the relevant intrinsic organization. We therefore define a mechanism-enriched canonical structure and use it to formulate Intrinsic Causal-Computational Realization (ICCR), a realization relation preserving physical implementation, intrinsic state individuation, transition structure, intervention profiles, and the relevant agent-body-world boundary. The central result is conditional: if conscious properties are invariants of intrinsic causal-computational organization, then any system satisfying ICCR realizes the same consciousness-relevant properties, whether biological, artificial, or simulated. We discuss objections including biological naturalism and integrated information theory. We conclude that to deny consciousness to a simulation, one must identify a consciousness-relevant intrinsic causal-computational structure that the simulation fails to realize.

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References · 5

  1. 2023Consciousness in Artificial Intelligence: Insights from the Science of Consciousnesscited by 99
  2. 2022Integrated information theory (IIT) 4.0: Formulating the properties of phenomenal existence in physical termscited by 21
  3. 2024Dissociating Artificial Intelligence from Artificial Consciousnesscited by 7
  4. 2026Canonical Functionalism: Defining Functional Structure without Observer-Relative Semantic Mapscited by 1
  5. 2026Intrinsic Computational Functionalism: From Observer-Relative Maps to Observer-Independent Structurescited by 1

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