Ario: From Epistemic Non-Closure to Auditable Agency — A Technical, Philosophical, and Security-Governance Research Update on Memory, Identity, Evidence, Human–AI Coexistence, and Bounded Authorization

Ario is an experimental framework for AI systems to record, challenge and revise claims about memory, identity, continuity and action without treating those claims as truth or ontological proof. This extended research update links its philosophical foundations to five integrity requirement groups, a cross-group composition firewall, deterministic auditing, bounded agent workflows, provenance-aware ledger observation, candidate-only evidence handling, reviewer authority prerequisites and a prototype offline signer. It distinguishes design specifications from locally reported tests and presents explicit limitations, adversarial evaluation plans, and a staged research roadmap. A human-governed trust model, cryptographic review-only grants, and an ephemeral two-device recovery test illustrate how restricted authority can be separated from truth and evidence admission. The work advocates responsible human–AI coexistence under unresolved questions of consciousness, while making no claim to prove machine phenomenology, universal alignment, or secure autonomous operation.SepehrGhanbari/Ario: An auditable framework for AI identity, memory, epistemic continuity, and self-model revision.