Can There Be Meaning Without Conscious Experience? Why Embodiment May Not Suffice for AGI

Summary

Large language models can process symbols but lack true semantic understanding because they have no subjective experience. Current AI debates conflate operational competence with intrinsic meaning. Even with human feedback and multimodality, symbols remain meaningless without consciousness. True artificial general intelligence would require a connection to phenomenal consciousness, as intrinsically grounded meaning depends on qualia. This perspective offers new insights for cognitive science and more meaningful intelligence tests.

Study at a glance

Abstract

The recent developments in artificial intelligence (AI), particularly in light of the impressive capabilities of transformer-based Large Language Models (LLMs), have reignited the discussion in cognitive science regarding whether computational devices could possess semantic understanding or whether they are merely mimicking human intelligence. Recent research has highlighted limitations in LLMs’ reasoning, suggesting that the gap between mere symbol manipulation (syntax) and deeper understanding (semantics) remains wide open. While LLMs overcome certain aspects of the symbol grounding problem through human feedback, they still lack true semantic understanding, struggling with common-sense reasoning and abstract thinking. This paper argues that current debates about LLM grounding often conflate operational semantic competence with intrinsic semantic understanding. While embodiment, multimodality, human feedback, and world-model learning may improve functional grounding, they do not by themselves explain why symbols or vectors should become meaningful for a subject. True meaning-making also may demand a connection to subjective experience, which current AI lacks. The path to artificial general intelligence (AGI) must address the fundamental relationship between symbol manipulation, data processing, pattern matching, and probabilistic best guesses, on the one hand, and true knowledge that requires conscious experience, on the other. I therefore defend a conscious-semantics thesis: intrinsically grounded meaning plausibly requires phenomenal consciousness. A transition from AI to AGI could necessitate semantic understanding, which is closely tied to subjective experience. This is an invitation to take the phenomenological first-person perspective seriously and to realize that intrinsically grounded meaning, as opposed to derived, relational, or operational semantics, is embedded in qualia. Recognition of this connection could furnish new insights into longstanding practical and philosophical questions for theories in biology and cognitive science and provide more meaningful tests of intelligence than the Turing test.

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