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Algorithmic AI Consciousness

Kimpton-Nye, Samuel
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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 which 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 behaviours of current AI systems as evidence of consciousness.
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