Algorithmic AI Consciousness
Samuel Kimpton‐Nye
Philosophy and Phenomenological Research August 19, 2026 DOI: 10.1111/phpr.70155 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Key points | Argues that the algorithmic nature of AI systems does not prevent them from being conscious, proposing a mutual ontological dependence between dispositional and phenomenal properties that offers a physicalist account of AI consciousness. |
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.