{"ID":2885758,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.04383","arxiv_id":"2508.04383","title":"Artificial Consciousness as Interface Representation","abstract":"Whether artificial intelligence (AI) systems can possess consciousness is a contentious question because of the inherent challenges of defining and operationalizing subjective experience. This paper proposes a framework to reframe the question of artificial consciousness into empirically tractable tests. We introduce three evaluative criteria - S (subjective-linguistic), L (latent-emergent), and P (phenomenological-structural) - collectively termed SLP-tests, which assess whether an AI system instantiates interface representations that facilitate consciousness-like properties. Drawing on category theory, we model interface representations as mappings between relational substrates (RS) and observable behaviors, akin to specific types of abstraction layers. The SLP-tests collectively operationalize subjective experience not as an intrinsic property of physical systems but as a functional interface to a relational entity.","short_abstract":"Whether artificial intelligence (AI) systems can possess consciousness is a contentious question because of the inherent challenges of defining and operationalizing subjective experience. This paper proposes a framework to reframe the question of artificial consciousness into empirically tractable tests. We introduce t...","url_abs":"https://arxiv.org/abs/2508.04383","url_pdf":"https://arxiv.org/pdf/2508.04383v1","authors":"[\"Robert Prentner\"]","published":"2025-08-06T12:25:06Z","proceeding":"cs.AI","tasks":"[\"cs.AI\",\"q-bio.NC\"]","methods":"[]","has_code":false}