Biological computationalism (why computers won't be conscious)

Informal presentation: Consciousness May Require a New Kind of Computation, Neuroscience News, December, 23, 2025.

Summary: A new theoretical framework argues that the long-standing split between computational functionalism and biological naturalism misses how real brains actually compute.

The authors propose “biological computationalism,” the idea that neural computation is inseparable from the brain’s physical, hybrid, and energy-constrained dynamics rather than an abstract algorithm running on hardware. In this view, discrete neural events and continuous physical processes form a tightly coupled system that cannot be reduced to symbolic information processing.

The theory suggests that digital AI, despite its capabilities, may not recreate the essential computational style that gives rise to conscious experience. Instead, truly mind-like cognition may require building systems whose computation emerges from physical dynamics similar to those found in biological brains.

Key Facts:

• Hybrid Dynamics: Brain computation arises from discrete spikes embedded within continuous chemical and electrical fields.
• Multi-Scale Coupling: Neural processes remain deeply intertwined across levels, meaning algorithms cannot be separated from physical implementation.
• Energetic Constraints: Metabolic limits shape neural computation, influencing learning, stability, and information flow.

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Research Article: Borjan Milinkovic, Jaan Aru, On biological and artificial consciousness: A case for biological computationalism, Neuroscience & Biobehavioral Reviews, Volume 181, 2026, 106524, ISSN 0149-7634, https://doi.org/10.1016/j.neubiorev.2025.106524.

Abstract: The rapid advances in the capabilities of Large Language Models (LLMs) have galvanised public and scientific debates over whether artificial systems might one day be conscious. Prevailing optimism is often grounded in computational functionalism: the assumption that consciousness is determined solely by the right pattern of information processing, independent of the physical substrate. Opposing this, biological naturalism insists that conscious experience is fundamentally dependent on the concrete physical processes of living systems. Despite the centrality of these positions to the artificial consciousness debate, there is currently no coherent framework that explains how biological computation differs from digital computation, and why this difference might matter for consciousness. Here, we argue that the absence of consciousness in artificial systems is not merely due to missing functional organisation but reflects a deeper divide between digital and biological modes of computation and the dynamico-structural dependencies of living organisms. Specifically, we propose that biological systems support conscious processing because they (i) instantiate scale-inseparable, substrate-dependent multiscale processing as a metabolic optimisation strategy, and (ii) alongside discrete computations, they perform continuous-valued computations due to the very nature of the fluidic substrate from which they are composed. These features – scale inseparability and hybrid computations – are not peripheral, but essential to the brain’s mode of computation. In light of these differences, we outline the foundational principles of a biological theory of computation and explain why current artificial intelligence systems are unlikely to replicate conscious processing as it arises in biology.