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Grounded Computation & Consciousness: A Framework for Exploring Consciousness in Machines & Other Organisms

Ryan Williams

arXiv Preprint Archive September 24, 2024 via arXiv

Summary

AI-generated from the abstract

Computational models alone may be insufficient for fully understanding consciousness; an ontological foundation is also needed. A formal framework is introduced that grounds computational descriptions in an ontological substrate, enabling estimation of differences in qualitative experience between two systems. The approach is broadly applicable to computational theories of consciousness.

Study at a glance

Characteristics Theoretical or philosophical paper Qualitative Peer reviewed
Keywords Consciousness awareness Sentience Artificial intelligence cs.ai Machine learning Neuroscience q-bio.nc
Key finding A formal framework is introduced that grounds computational descriptions in an ontological substrate, enabling estimation of differences in qualitative experience between two systems.

Abstract

Computational modeling is a critical tool for understanding consciousness, but is it enough on its own? This paper discusses the necessity for an ontological basis of consciousness, and introduces a formal framework for grounding computational descriptions into an ontological substrate. Utilizing this technique, a method is demonstrated for estimating the difference in qualitative experience between two systems. This framework has wide applicability to computational theories of consciousness.

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