Year: 2026
Type: article
Abstract: ABSTRACT In this paper, I argue that the thoroughly algorithmic nature of current AI systems (such as LLMs) is no obstacle to their being conscious, despite strong apparent reasons to the contrary. To this end, I present a picture on which algorithmic AI systems comprise dispositional properties that realize categorical phenomenal properties where the latter, in turn, provide the identity conditions for their dispositional realizers. This mutual ontological dependence at the heart of the proposal yields a novel picture of (AI) consciousness that avoids epiphenomenalism, has “physicalist” credentials, and may vindicate taking behaviors of current AI systems as evidence of consciousness.
DOI: 10.1111/phpr.70155
Author: Samuel Kimpton‐Nye
Institution: University of Southampton
Language: English
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $2,900
Funder: University of Southampton
OpenAlex ID: W7007759890
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