Standardized Definition of AI Governance (github.com)

A canonical public repository has published "The Standardized Definition of AI Governance (v1.0)" as an authoritative, citable standard: the PDF and markdown are the only canonical texts and define AI governance as a verifiable condition. The release bundles core materials — a glossary (Annex A), 15 Structural Tests for verification (Annex B), and a Certification & Continuous Verification framework (Annex C) — plus versioning, change-log, and a recommended citation. The maintainer (Russell Parrott) and licensing (CC BY-NC-ND 4.0) are explicit: redistribution with attribution is allowed but modifications to the core standard are not. This matters for the AI/ML community because it establishes a stable baseline for regulatory, contractual, and audit use: conformance must be measured against the canonical PDF and explicitly reference the 15 Structural Tests, while Annex C outlines ongoing certification and continuous verification practices. Practically, vendors, auditors, and regulators gain a single source of truth for what constitutes “AI governance” in verifiable terms, improving auditability, comparability, and interoperability of governance claims. The non-derivative license and strict canonical-file rule also aim to prevent fragmentation, ensuring that assessments and certifications reference the same unambiguous standard.