EU AI Act Alignment

The EU AIArtificial IntelligenceSystems that learn, adapt, and act with real-world impact Act (effective August 2, 2026) is the most comprehensive AIArtificial IntelligenceSystems that learn, adapt, and act with real-world impact regulation enacted to date. It maps article-by-article to Web4Web4Open governance ontology for trust-native entity interactionsprimitives — not as a compliance checklist bolted on after the fact, but as architectural satisfaction. The system is compliant by construction.

Article 9 — Risk Management: The Act requires continuous risk assessment throughout the AIArtificial IntelligenceSystems that learn, adapt, and act with real-world impact system lifecycle. Web4Web4Open governance ontology for trust-native entity interactionssatisfies this through T3/V3 continuous assessment — trust and value scores that update with every observed outcome. Risk is not assessed quarterly. It is measured with every action.

Article 13 — Transparency: The Act requires that AIArtificial IntelligenceSystems that learn, adapt, and act with real-world impact systems be designed to allow interpretation of output and enable oversight. Web4Web4Open governance ontology for trust-native entity interactionsprovides witnessed provenance chains — every action, every decision, every trust update is recorded with witnesses. The governance graph is the transparency mechanism.

Article 14 — Human Oversight: The Act requires that high-risk systems allow effective human oversight. Web4Web4Open governance ontology for trust-native entity interactionsimplements heuristics in the loop with escalation — governance frameworks present at decision time, with clear escalation paths when conditions exceed agent authority. Not “human in the loop” for every decision, but human-designed frameworks with human-accessible overrides.

Article 22 / GDPR Automated Decisions: The right to contest automated decisions. Web4Web4Open governance ontology for trust-native entity interactionsprovides the GOV-001 appeals process — a structured mechanism for challenging governance decisions with full provenance visibility. The entity can see exactly which trust scores, which witnesses, and which MRHMarkov Relevancy HorizonFractal context scoping — defines where governance applies boundaries led to the decision.

This is not retrofit compliance. The Web4Web4Open governance ontology for trust-native entity interactions ontology was not designed to satisfy the EU AIArtificial IntelligenceSystems that learn, adapt, and act with real-world impactAct. It was designed from biological governance principles. That it maps cleanly to regulatory requirements is evidence that the principles are sound — the regulation and the ontology converge because they are both attempting to solve the same problem from different starting points.