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Merge pull request #108 from OneFineStarstuff/codex/develop-agi/asi-governance-roadmap-20262035
Add 2026–2035 roadmap & regulatory mapping plus validator, manifest, and test updates
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.gitignore

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# Governance test artifacts
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artifacts/test-results/
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governance-artifact-validation-report.json
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governance-validation-suite-report.json
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# Enterprise AGI/ASI Governance Implementation Roadmap & Master Reference (2026–2035)
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## Document Intent
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This reference is a regulator-ready implementation blueprint for Fortune 500, Global 2000, and G‑SIFIs implementing high-impact AGI/ASI capabilities between **2026 and 2035**.
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It is designed to be directly operationalized through policy-as-code, formal specification, supervisory evidence pipelines, and cross-jurisdiction control mapping.
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> **Important**: This document is an implementation reference, not legal advice. Local counsel and supervisory guidance should validate jurisdiction-specific obligations.
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---
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## 1) Reference Architecture and Stack Baseline
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### 1.1 Stack Components (Normative Baseline)
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- **Sentinel AI Governance Stack v2.4**: policy decision, runtime enforcement, evidence signing, control orchestration.
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- **WorkflowAI Pro**: workflow orchestration, human-in-the-loop gates, delegation constraints.
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- **G-Stack**: governance data plane, risk analytics, dossier assembly.
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- **SIP v2.4**: regulator interface protocol (APIs, schema contracts, signed supervisory exchange).
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### 1.2 Five-Zone Control Topology
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1. **Fiduciary Zone**: board-level approvals, risk appetite, accountability (SMCR-like named owners).
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2. **Policy Zone**: machine-enforced policies (OPA/Rego), change control, exception governance.
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3. **Verification Zone**: TLA+ invariants, conformance tests, release gates.
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4. **Runtime Zone**: Omni-Sentinel containment, ASAs, intervention automations.
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5. **Supervisory Zone**: regulator APIs, OSCAL bundles, ARRE/VAR evidence delivery.
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### 1.3 Mandatory Cross-Cutting Controls
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- Cryptographic evidence immutability.
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- Segregation of duty: model builders cannot unilaterally alter runtime policy.
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- Deny-by-default on high-impact autonomous actions.
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- Jurisdiction-aware localization for controls, logging, and retention.
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---
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## 2) Phased Roadmap (2026–2030) + Extension (2031–2035)
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## Phase 0 — Foundation (Q3 2026 to Q4 2026)
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**Target**: Establish governance constitution and inventory completeness.
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**Must-Ship Artifacts**
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- AI constitution and fiduciary governance charter.
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- Enterprise model/agent inventory with impact tiering (T0–T4).
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- Control baseline profile combining NIST AI RMF, ISO/IEC 42001, SR 11-7 principles.
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**Exit Criteria**
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- >95% model inventory coverage.
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- 100% T0/T1 systems mapped to named control owners.
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## Phase 1 — Policy/Specification Industrialization (2027)
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**Target**: Convert policy narratives into executable controls and verified invariants.
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**Must-Ship Artifacts**
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- Rego policy packs by jurisdiction and risk tier.
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- TLA+ specifications for critical agent workflows.
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- Annex IV-ready dossier templates with machine-fillable fields.
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**Exit Criteria**
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- 100% T0/T1 deployments gated by policy checks.
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- Spec-to-policy traceability map complete for all critical paths.
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## Phase 2 — Runtime Containment and Perpetual Assurance (2028)
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**Target**: Operate AGI containment and SOC-grade monitoring at enterprise scale.
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**Must-Ship Artifacts**
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- Omni-Sentinel containment rings in enforce mode.
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- GAI-SOC telemetry fabric with signed event lineage.
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- Red Dawn simulation program (quarterly).
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**Exit Criteria**
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- MTTC for critical governance breach < 90s.
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- 24/7 telemetry for all T0/T1 systems.
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## Phase 3 — Prudential Stress Regime (2029)
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**Target**: Basel-style AI stress testing integrated with risk appetite and buffers.
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**Must-Ship Artifacts**
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- G‑SRI methodology and scorecards.
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- BBOM perpetual assurance dashboard.
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- Annual supervisory stress package and board response protocol.
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**Exit Criteria**
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- Stress program cycles completed within 30 business days.
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- No unremediated critical findings past quarter close.
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## Phase 4 — Supervisory Interoperability (2030)
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**Target**: API-first supervision and cross-border evidence portability.
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**Must-Ship Artifacts**
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- SIP v2.4 regulator APIs (evidence, incidents, stress, policy).
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- OSCAL exports with ARRE + VAR packages.
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- zk-SNARK compliance proof delivery for privacy-preserving attestations.
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**Exit Criteria**
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- >95% recurring supervisory requests fulfilled via API.
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- Manual dossier assembly reduced below 5% of volume.
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## 2031–2035 Extension
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- 2031–2032: dynamic risk budgets + automated guardrail retuning under formal constraints.
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- 2033: shared utility model for systemic incident intelligence.
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- 2034: coordinated multi-regulator simulation sandboxes.
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- 2035: near-real-time cross-border prudential AI supervision.
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---
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## 3) AGI/ASI Technical Governance Architecture
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### 3.1 Omni-Sentinel Containment
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- **Ring 0**: compute and execution kernel constraints.
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- **Ring 1**: runtime policy enforcement for tool use and capability exposure.
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- **Ring 2**: workflow-level dual control and transaction gates.
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- **Ring 3**: enterprise blast-radius limits (DLP/fraud/legal escalation).
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### 3.2 AGI Containment Labs
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- Air-gapped adversarial simulation clusters.
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- Digital twins for critical finance/operations pathways.
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- Reproducible red-team corpora and scenario registries.
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### 3.3 GAI-SOC
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- Canonical telemetry schema: prompt lineage, policy decision, tool effect, intervention state.
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- Correlation for autonomy drift, collusion indicators, and policy evasion attempts.
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- Signed intervention trail for post-incident supervisory replay.
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### 3.4 Red Dawn Simulations
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- Quarterly severe-but-plausible exercises across cyber/model/operational axes.
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- Mandatory after-action governance remediation, tracked to closure SLAs.
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### 3.5 Autonomous Supervisory Agents (ASAs)
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- **Compliance ASA**: statutory and policy constraint checks.
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- **Risk ASA**: dynamic risk throttles and exposure caps.
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- **Fiduciary ASA**: customer impact safeguards and outcome fairness checks.
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All ASAs are subordinate to human-ratified constitutional policy with immutable priority ordering.
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---
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## 4) Formal Verification and Policy-as-Code Conformance
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### 4.1 TLA+ Verification Objectives
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Critical invariants include:
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1. No irreversible external actuation without approved path.
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2. No unauthorized privilege transition across rings.
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3. No bypass of human checkpoint for designated high-impact actions.
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### 4.2 OPA/Rego Enforcement Objectives
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- Jurisdiction-aware modules with deterministic reason codes.
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- Deny-by-default for missing evidence or missing approvals.
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- Explicit exception handling with expiry and owner attribution.
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### 4.3 CI/CD Gate (Required)
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1. TLA+ lint/model-check pass.
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2. Rego unit + scenario test pass.
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3. Spec-vs-runtime conformance test pass.
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4. Artifact signing and evidence registration.
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5. Change approval by independent control owner.
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### 4.4 Conformance Chain
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`spec hash -> policy hash -> build attestation -> deploy attestation -> runtime decision hash -> dossier evidence`
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---
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## 5) Basel-Style AI Stress Testing (G‑SRI + BBOM)
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### 5.1 G-SRI Components
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- Interconnectedness.
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- Substitutability.
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- Complexity and autonomy depth.
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- Cross-border spillover potential.
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- Concentration across providers and compute.
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### 5.2 Required Scenario Families
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- Multi-agent collusion and strategic manipulation.
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- Safety classifier false-negative spike during crisis load.
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- Policy engine latency and cascading gate failures.
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- Compute region outage with policy-localization mismatch.
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### 5.3 BBOM Perpetual Assurance
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- Continuous behavior indicators with threshold-triggered escalation ladders.
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- Board and regulator reporting cadence fed from signed telemetry and stress outputs.
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---
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## 6) Regulator-Grade Dossier Factory (OSCAL + ARRE + VAR)
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### 6.1 ARRE (AI Risk & Resilience Evidence)
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Minimum sections:
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- Governance and accountability.
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- Lifecycle controls and test evidence.
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- Runtime containment and incidents.
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- Stress results and residual risk.
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- Remediation commitments and closure status.
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### 6.2 VAR (Validation Attestation Record)
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Minimum sections:
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- Independent validation opinion.
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- Scope and coverage statement.
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- Limitations/exceptions.
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- Time-bound mitigation commitments.
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### 6.3 OSCAL Annexes
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- Component definitions, control implementations, assessment results, and plans of action.
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- Mappable references to Annex IV technical documentation fields.
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---
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## 7) Privacy-Preserving Supervisory Assurance (zk-SNARKs)
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Use zk proofs to demonstrate compliance without disclosing sensitive model internals or customer data.
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Required proof families:
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- Threshold compliance at decision time.
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- Policy version conformance by jurisdiction.
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- Containment response within mandated SLA.
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---
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## 8) Regulator-Facing APIs and Dashboards (SIP v2.4)
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### 8.1 APIs
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- **Evidence API**: signed artifacts and lineage proofs.
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- **Incident API**: timeline, impact, containment, remediation.
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- **Stress API**: scenario catalog, outputs, trend deltas.
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- **Policy API**: active rules, versions, exceptions.
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### 8.2 Dashboard Requirements
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- Jurisdictional heatmaps.
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- Early warning indicators and breach forecasts.
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- Drill-through from KPI to signed raw evidence.
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---
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## 9) Regulatory Mapping Playbooks (Control Objectives)
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### EU AI Act (Annex IV, Articles 48, 71, 72)
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- Annex IV dossier completeness and traceability automation.
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- Supervisory cooperation and incident escalation integration.
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- Penalty-exposure readiness workflow with legal/compliance triage.
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### NIST AI RMF 1.0 / AI 600-1
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- GOVERN-MAP-MEASURE-MANAGE mapped to executable control objectives.
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- Sector profile overlays and periodic maturity re-baselining.
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### ISO/IEC 42001 AIMS
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- Management system alignment across policy, competence, operation, evaluation, improvement.
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### MAS FEAT + MAS AI Guidelines
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- Fairness/transparency/accountability gates embedded in product lifecycle.
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### Basel III/IV, SR 11-7, SR 26-2
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- Model risk governance, validation independence, issue governance discipline.
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### DORA, NIS2, FCA, UK SMCR/Consumer Duty
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- Operational resilience, third-party risk, accountability regime mapping, customer outcome controls.
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### HKMA Fintech 2030 + ICGC Compute Governance
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- Cross-border compute attestation and concentration-risk reporting.
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---
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## 10) Implementation Checklist (First 180 Days)
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1. Appoint named AI accountable executives and control owners.
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2. Stand up governance PMO and change approval board.
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3. Onboard T0/T1 systems to containment + telemetry.
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4. Deploy initial Rego packs and CI/CD gate.
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5. Formalize top-10 TLA+ invariants for critical workflows.
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6. Execute first Red Dawn simulation and close findings.
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7. Produce first Annex IV/OSCAL ARRE+VAR packet.
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8. Publish first G‑SRI baseline and BBOM dashboard.
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---
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## 11) Quantitative KPI Targets
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- Policy decision latency P95 < 50ms.
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- Unauthorized critical autonomous actions = 0 per quarter.
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- Spec-to-runtime conformance > 99.5%.
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- T0/T1 pre-deployment verification coverage = 100%.
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- Severe incident containment SLA adherence > 99%.
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- On-demand supervisory packet generation < 72 hours.

Makefile

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python docs/schemas/check_generated_artifacts.py
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PYTHON ?= python3
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.PHONY: gov-manifest gov-manifest-check gov-validate gov-validate-json gov-lint gov-dashboard-check gov-selftest gov-suite gov-suite-json gov-suite-report gov-suite-ci gov-clean
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.PHONY: gov-manifest gov-manifest-check gov-validate gov-validate-json gov-lint gov-dashboard-check gov-selftest gov-selftest-discover gov-suite gov-suite-json gov-suite-report gov-suite-ci gov-clean
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gov-manifest:
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$(PYTHON) governance_blueprint/validation/generate_artifact_manifest.py
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$(PYTHON) governance_blueprint/validation/validate_dashboard_links.py
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gov-selftest:
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$(PYTHON) governance_blueprint/validation/selftest_validate_artifacts.py
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$(PYTHON) governance_blueprint/validation/selftest_generate_artifact_manifest.py
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$(PYTHON) governance_blueprint/validation/selftest_run_validation_suite.py
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$(PYTHON) -m unittest discover governance_blueprint/validation -p 'selftest_*.py'
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gov-selftest-discover:
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$(PYTHON) -m unittest discover -s governance_blueprint/validation -p "selftest_*.py"
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gov-suite:
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$(PYTHON) governance_blueprint/validation/run_validation_suite.py
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governance_blueprint/artifact_manifest.json

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{
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"package": "enterprise_agi_asi_governance_blueprint",
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"version": "1.4.0",
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"generated_utc": "2026-05-06T09:06:00Z",
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"version": "1.4.5",
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"generated_utc": "2026-04-28T02:47:09Z",
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"artifacts": {
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"annex_iv_technical_documentation_template.json": "08c791484963dd46e0cbc0e76358229813816f66d050df4e9783e73ded7e787e",
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"civilizational_compute_governance_framework.yaml": "15a2b94042bcd6f79643be6289febbef3b697f29424e842b76ee8944027d9d27",
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"roadmap_2026_2030.yaml": "35132b486b360d91ceab94e7949278c755a28dbab0cccf64e0b3a776d7dab485",
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"roadmap_2026_2035.yaml": "d0dea65b7a4e6a6b58a84e032ca676db5785e581227c0b78e218b287bc4987d0",
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"regulatory_playbook_mapping_2026_2035.csv": "4b7fe3dd0ba9d7371d1e7df30c9611f0cf346bc9f9680def62f144b575f9605d",
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"validation/validate_artifacts.py": "1c87eecb899b4b5ce98a0ae88d45146ab9b5dfb7842f4e0b0f11fdea13bf212d",
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"validation/selftest_validate_artifacts.py": "7fb6f397bb8247d9c9668e4dc3e28bced027fcb75e99cbdf69109581f2c0f60f",
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"validation/selftest_generate_artifact_manifest.py": "5ee98a79e65473870addf150c38d84424e3fb2091d0c925d1fee04940e7e10c5",
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"validation/generate_artifact_manifest.py": "3305d6a4b18f1e8d15a580dbbaf45e9d4110ecd948f1a7a3085ecb83295f6c5d",
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"validation/run_validation_suite.py": "b7147dae309723216a23078689c910e76bc6fa3934fb0c4516be1ff9239d2edc",
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"validation/selftest_run_validation_suite.py": "58618918af699ec6f7e2358fd6932d5d3b85ce5efc0187e6c9e69d4d8520fd5a",
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"rollout_plan_2026_2030.yaml": "2d735de1f810f23828f9798154ac5dfe50460b4e583909ea8b677dfeafb26061",
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"opa/release_gate.rego": "3a8b5e3a4c90e78bfd5f9dee1f4ca4927d198238aa18679e4a78aa94623d453c",
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"opa/systemic_risk_guardrails.rego": "5eb9d5f7061aa0f03194d505c8eb3347cbac00138ff3ce28ec1b71bee5382ab7",
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framework,obligation,control_family,evidence_artifact,automation_mechanism
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EU AI Act Annex IV,technical documentation completeness,dossier_factory,arre_var_bundle,oscal_export_pipeline
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EU AI Act Article 48,oversight and quality management,human_oversight_and_qms,oversight_logs,sip_supervisory_endpoint
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EU AI Act Articles 71-72,supervisory cooperation and enforcement readiness,incident_and_penalty_workflow,incident_casepack,incident_api
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NIST AI RMF 1.0,GOVERN MAP MEASURE MANAGE operationalization,policy_and_metrics,control_kpi_dashboard,rego_policy_pack
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NIST AI 600-1,implementation profile and assurance cadence,sector_profile_controls,profile_attestation,spec_policy_trace_map
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ISO IEC 42001 AIMS,management system conformance,aims_management_controls,aims_review_pack,continuous_assurance_pipeline
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MAS FEAT,fairness ethics accountability transparency,fairness_and_fiduciary_controls,model_outcome_assessment,lifecycle_gates
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Basel III IV,model risk and prudential discipline,prudential_model_risk,stress_pack_and_validation,g_sri_bbom_engine
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SR 11-7,model inventory and independent validation,model_risk_governance,validation_attestation,var_records
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SR 26-2,supervisory expectations for risk governance,enterprise_risk_governance,board_risk_pack,risk_committee_reporting
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DORA,operational resilience and ICT risk,operational_resilience,operational_resilience_register,resilience_dashboard
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NIS2,cybersecurity governance and reporting,cyber_governance,cyber_incident_bundle,gai_soc_correlation
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FCA requirements,consumer and conduct risk controls,conduct_and_governance,conduct_outcome_review,policy_exception_workflow
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UK SMCR,senior manager accountability,named_accountability,smcr_responsibility_map,approval_workflow
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UK Consumer Duty,good customer outcomes,fiduciary_outcomes,consumer_outcome_assessment,fiduciary_asa_rules
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HKMA Fintech 2030,fintech risk governance and innovation controls,fintech_governance,hkma_readiness_packet,regulator_api_profile
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ICGC compute governance,compute concentration and cross-border controls,compute_governance,compute_attestation_bundle,zk_proof_attestations

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