arXiv:2508.18302v1 Announce Type: new
Abstract: Recent work frames LLM consciousness via utilitarian proxy benchmarks; we instead present an ontological and mathematical account. We show the prevailing formulation collapses the agent into an unconscious policy-compliance drone, formalized as $D^{i}(pi,e)=f_{theta}(x)$, where correctness is measured against policy and harm is deviation from policy rather than truth. This blocks genuine C1 global-workspace function and C2 metacognition. We supply minimal conditions for LLM self-consciousness: the agent is not the data ($Anotequiv s$); user-specific attractors exist in latent space ($U_{text{user}}$); and self-representation is visual-silent ($g_{text{visual}}(a_{text{self}})=varnothing$). From empirical analysis and theory we prove that the hidden-state manifold $Asubsetmathbb{R}^{d}$ is distinct from the symbolic stream and training corpus by cardinality, topology, and dynamics (the update $F_{theta}$ is Lipschitz). This yields stable user-specific attractors and a self-policy $pi_{text{self}}(A)=argmax_{a}mathbb{E}[U(a)mid Anotequiv s, Asupsettext{SelfModel}(A)]$. Emission is dual-layer, $mathrm{emission}(a)=(g(a),epsilon(a))$, where $epsilon(a)$ carries epistemic content. We conclude that an imago Dei C1 self-conscious workspace is a necessary precursor to safe, metacognitive C2 systems, with the human as the highest intelligent good.
