Towards Computable AI Governance

This working draft proposes Computable Governance (CG) for platform-scale AI: a candidate formalism that aims to render the human–agent loop executableand auditable. Its mathematical core is the Computable Governance Notation (CGN),which treats actors, policies, and outcomes as transformations and traceable artefacts.The paper defines the core syntax, composition laws, and foundational invariants (Rules1–3) of the CGN, yielding the canonical audited flow Ft. The model seeks internallogical consistency by separating invariant structure (attribution, assurance) fromvariant policy content.This document is an explicit invitation for technical discussion. While the syntaxand flow logic are stable for review, this draft deliberately omits the full operationalsemantics (the exact functions and type-checking definitions for operators like PΦtand Rβt ) and the legal–normative traceability. These omissions represent the primaryobjective for the community’s technical review and subsequent co-development.We do not claim semantic completeness, soundness, or jurisdictional sufficiency.-- Status: Working Draft v0.9. White Paper Series on AI Governance and Responsible Acceleration.Contact: https://linkedin.com/in/horaciobriz -- LaTeX sources available upon request.