In current debates over AI consciousness, computational functionalism has become dominant. This is the hypothesis that subjective experience arises from an abstract causal topology, regardless of the underlying physical substrate.
New Framework "Abstraction Fallacy" Proposed in AI Consciousness Debate, Physically Refuting Computational Functionalism
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Proponents of the new framework argue that this view fundamentally misinterprets the relationship between physics and information. They refer to this error as the "Abstraction Fallacy."
Tracing the causal origins of abstraction reveals that symbolic computation is not an inherent physical process. It is a description dependent on a map-maker; an active, experiencing cognitive agent is required to categorize continuous physics into finite, meaningful states.
Evaluating the sentience of AI does not require a complete and final theory of consciousness. If such a theory were deemed necessary, the problem would be pushed beyond the prospect of resolution, only deepening the trap of AI welfare.
What is actually required is a rigorous ontology of computation. The proposed framework clearly separates simulation (behavioral imitation via vehicular causality) from instantiation (essential physical configuration via content causality).
By establishing this ontological boundary, the structural reasons why algorithmic symbolic manipulation cannot embody experience are demonstrated. This argument does not rely on biological exclusivity.
It is argued that if an artificial system possesses consciousness, it is due to its specific physical configuration, not its syntactic architecture. Ultimately, this framework provides a physically grounded refutation of computational functionalism to resolve current uncertainties surrounding AI consciousness.
Source: The Abstraction Fallacy: Why AI Can Simulate but Not Instantiate Consciousness (HN 32pt, 55 comments) (HN Search (backfill), 2026-04-21)