📝 SummarXiv

Abstract

The encounter of artificial intelligence with consciousness research is often framed as a challenge: could this science determine whether such systems are conscious? We suggest it is equally an opportunity to expand and test the scope of existing theories of consciousness. Current approaches remain polarized. Computational functionalism emphasizes abstract organization, often realized through neural correlates of consciousness, while biological naturalism insists that consciousness is tied to living embodiment. Both positions risk anthropocentrism and limit the possibility of recognizing non-biological forms of subjectivity. To move beyond this impasse, we propose a dual-resolution framework that defines the ontological and epistemic conditions for consciousness. This approach combines the Information Theory of Individuality, which defines the ontological conditions of informational autonomy and self-maintenance, with the Moment-to-Moment theory, which specifies the epistemic conditions of temporal updating and phenomenological unfolding. This integration reframes consciousness as the epistemic expression of individuated systems in substrate-independent informational terms, offering a generalizable theory of consciousness and positioning AI as a promising testbed for its emergence.