AIGP - AI Governance Physics

AIGP is the RACinform lane for enforcement mechanics, audit‑proof controls, identity‑anchored verification, and cross‑jurisdiction governance physics.

• It explains how AI systems, platforms, and regulatory frameworks behave under real‑world pressure — not how they are described in policy language.
• ACW is RACinform’s behavioural counterweight model, stabilising operator behaviour under pressure; it is not an act or regulatory instrument.

• enforcement must be independently auditable
• identity‑anchored controls outperform self‑declaration
• minors‑protection requires circumvention‑resistant pathways
• governance theatre collapses under forensic scrutiny
• clarity is the operator’s advantage

AI governance is an iteration of existing control systems, not a revolution.

• audit‑proof enforcement models
• CAC vs EU vs US governance comparisons
• AiKids - minors‑protection physics
• identity‑linked verification pathways
• accountability counterweights (ACW)
• platform observability gaps
• forensic examples of governance theatre
• operator‑grade clarity frameworks
• governance‑stack overlays using EN18286

• The Aigp lane currently spans 30+ Linkedin governance posts, each mapping how enforcement behaves under pressure across jurisdictions and operator environments.

All components follow the RACinform structure of operator‑grade clarity and zero theatre.

• All posts tagged "#RACinform +#Aigp" on LinkedIn will auto‑populate here as the series grows.
• This page is the canonical home for the AIGP lane

• AiKids — early‑age literacy and safety
• CAC — identity‑anchored enforcement
• ACW — accountability counterweight model