Executive Overview
+Real-time dashboard summarizing all 12 domains of AISAFETY-GOVNAV-WP-027 — AI safety risk taxonomy, global governance frameworks, stakeholder mapping, implementation roadmap, product features, and cross-cutting regulatory compliance.
+ +Compliance Radar — Regulatory Framework Scores
+Key Categories of AI Safety Risks
+Comprehensive taxonomy of AI safety risks: intentional misuse, unintended consequences, existential threats, privacy exploitation, and accountability gaps. Each category includes sub-risks, severity ratings, likelihood assessments, example scenarios, OPA/Sentinel rule counts, and regulatory references.
+ + + + +Risk Matrix Summary
+ +Global AI Safety Governance Frameworks
+Analysis of three governance mechanism types: international treaties (Bletchley, Seoul, proposed UN Convention), multi-stakeholder initiatives (OECD, PAI, GPAI), and adaptive regulatory bodies (EU AI Office, UK AISI, US NIST + EO 14110). Assessed for strengths, weaknesses, and implementation challenges.
+ + + +Comparative Assessment
+ +Key Stakeholders in AI Safety Governance
+Mapping of 6 stakeholder groups: governments, international organizations, AI developers, researchers, civil society, and the general public. Each stakeholder details roles, responsibilities, contributions, influence level, and challenges.
+ + +Implementation Roadmap
+Prioritized, dependency-aware roadmap: 4 phases, 19 milestones, 30 weeks, $14.0M budget. Features grouped by AI assistant, accessibility, governance reporting, prompt analysis, task management, and safety/telemetry. Cross-cutting: RBAC (53%), Active Learning (42%), Compliance (74%).
+ + + + +Dependency Graph
+ + +Feature Group Mapping
+ +Model Registry
+Centralized registry for 847 AI models with configurations, performance metrics, lineage tracking, and research-domain links. Schema with 13 fields covering UUID, version, type, tier, status, configuration, metrics, lineage, and compliance mapping.
+ + + +Advanced Prompt Engineering Studio
+Dedicated UI for constructing, testing, and optimizing prompts with real-time safety scoring (toxicity, bias, PII, injection risk), clarity analysis, template library (47 templates), A/B testing, and full version history.
+ + +Compliance Dashboard
+Maps 312 production models and 847 reports to EU AI Act (88 controls), NIST AI RMF (19 subcategories), and ISO 42001 (38 clauses). Configurable risk thresholds with green/yellow/red indicators.
+ + + +Risk Thresholds
+ + +Regulatory Product Mappings
+ +Telemetry, PID Alignment & Merkle Audit
+Comprehensive monitoring: 6-level safety status, PID controller (Kp/Ki/Kd) for alignment tuning, behavioral anomaly detection (5-sigma threshold), and Merkle-root-based audit log integrity with 12.4M leaves and SHA-256 hash chain.
+ +Safety Status Checks
+ + +PID Alignment Controller
+ + +Merkle Audit Log
+ +Role-Based Access Control
+Hierarchical RBAC: 7 roles, 42 permissions, 5 enforcement points. Roles from Board Member (Level 1) to Auditor (Level 6) with MFA, session timeout, and data scope controls.
+ + +Active Learning Loops
+5 continuous improvement loops: Compliance Accuracy (3.2% monthly gain), Prompt Effectiveness, Model Drift Response (MTTR 4.3h), Safety Incident Learning (67% auto-remediation), and Stakeholder Feedback (NPS 42 to 67).
+ + + +Version Control & PDF Export
+Git-inspired versioning for reports (3,247 versions), model configs (8,412), policy docs (1,842), prompt templates (612). Enhanced PDF export with 5 compliance-focused layouts and Merkle-chain evidence integration.
+ +