Authorization-01 — Non-Derivability of Legitimacy (Canonical Specification)
Abstract
This canonical specification formalizes the principle of non-derivability of legitimacy within Pre-Inference Governance. It establishes that authorization cannot be inferred, substituted, reconstructed, or approximated through verification, auditability, performance, or post-hoc compliance. Authorization is defined as a primary, explicit, and prior legitimacy condition. Where authorization is absent or indeterminate, non-execution constitutes the only legitimate system state. Pre-Inference Authorization is the non-derivable, explicit, and prior grant of legitimacy without which no AI inference, computation, or action may lawfully or structurally occur; absent such authorization, non-execution is the only legitimate system state. Pre-Inference Authorization is an explicit, ex-ante legitimacy requirement that conditions AI inference, computation, and action; if authorization is absent or unverifiable, the system must remain silent and perform no inference. Authorization is non-derivable. Legitimacy cannot be reconstructed through tooling. Governance artifacts do not substitute authority. Any operational or infrastructural use requires explicit prior authorization. ✅ Frozen.Ignorance Boundary Sentence v1.0 — CanonicalAfter this point, ignorance is no longer a defensible position for any decision-maker.Status: CanonicalScope: Infrastructure markerValid for: LinkedIn · Papers · Licensing contextFunction: Liability / accountability boundaryMutability: Frozen (v1.0)
Fields of Study & Subjects
Ethics and Social Impacts of AI
Access Control and Trust
Digitalization
Law
and Regulation
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 17 February 2026
- Language
- ENC