Kimpton-Nye, Samuel (2025) Algorithmic AI Consciousness. [Preprint]

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Abstract

I argue that the thoroughly algorithmic nature of current AI systems (such as LLMs) is no obstacle to their being conscious. To this end, I present a picture on which current AI systems comprise dispositional properties which realize categorical phenomenal properties where the latter, in turn, provide the identity conditions for their dispositional realizers. This mutual ontological dependence, or, symmetrical grounding, at the heart of the proposal yields a novel picture of (AI) consciousness that avoids epiphenomenalism and is more permissive regarding the specific nature/functional organization of conscious systems than has been previously suggested. This, in turn, suggests an epistemology of AI consciousness focused on investigating the high-level behaviours of AI systems rather than their low-level functional organization.

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Item Type:	Preprint
Creators:	Creators Email ORCID Kimpton-Nye, Samuel 0000-0001-9774-7247
Keywords:	Algorithms; Artificial Intelligence; Consciousness; Dispositions; Grounding; Large Language Models
Subjects:	Specific Sciences > Artificial Intelligence Specific Sciences > Cognitive Science > Consciousness
Depositing User:	Dr Samuel Kimpton-Nye
Date Deposited:	11 Apr 2025 15:05
Last Modified:	11 Apr 2025 15:05
Item ID:	25045
Subjects:	Specific Sciences > Artificial Intelligence Specific Sciences > Cognitive Science > Consciousness
Date:	11 April 2025
URI:	https://philsci-archive.pitt.edu/id/eprint/25045

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