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9 changes: 4 additions & 5 deletions Makefile
Original file line number Diff line number Diff line change
Expand Up @@ -49,12 +49,12 @@ lint-gsifi-governance:
npx --yes markdownlint-cli@0.39.0 --config docs/reports/.markdownlint.json docs/reports/GSIFI_AGI_ASI_GOVERNANCE_BLUEPRINT_2026_2030.md docs/reports/GSIFI_GOVERNANCE_ARTIFACTS_RUNBOOK.md

check-gsifi-governance: validate-gsifi-governance validate-gsifi-governance-module test-gsifi-governance lint-gsifi-governance
.PHONY: governance-test governance-validate governance-validate-json governance-validate-json-check governance-check
.PHONY: governance-test governance-reports-validate governance-validate-json governance-validate-json-check governance-check

governance-test:
python3 -m unittest discover tool_tests

governance-validate:
governance-reports-validate:
python3 tools/validate_governance_reports.py

governance-validate-json:
Expand All @@ -64,7 +64,7 @@ governance-validate-json-check:
python3 tools/validate_governance_reports.py --json > /tmp/governance_validation.json
python3 -c 'import json; p=json.load(open("/tmp/governance_validation.json", "r", encoding="utf-8")); assert p.get("status")=="passed", f"Validator JSON status not passed: {p}"; print("Validator JSON status is passed.")'

governance-check: governance-test governance-validate governance-validate-json-check
governance-check: governance-test governance-reports-validate governance-validate-json-check
.PHONY: governance-setup governance-deps-check governance-lint governance-validate governance-artifact-inventory governance-policy-test governance-validator-test governance-evidence-manifest governance-evidence-verify governance-evidence-schema governance-report governance-report-schema governance-check-generated

governance-setup:
Expand Down Expand Up @@ -140,8 +140,7 @@ gov-dashboard-check:
$(PYTHON) governance_blueprint/validation/validate_dashboard_links.py

gov-selftest:
$(PYTHON) governance_blueprint/validation/selftest_validate_artifacts.py
$(PYTHON) governance_blueprint/validation/selftest_run_validation_suite.py
$(PYTHON) -m unittest discover governance_blueprint/validation -p 'selftest_*.py'

gov-suite:
$(PYTHON) governance_blueprint/validation/run_validation_suite.py
Expand Down
193 changes: 193 additions & 0 deletions REGULATOR_READY_AGI_ASI_TECHNICAL_REPORT_2026_2030.md
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<title>Regulator-Ready 2026–2030 Enterprise and Civilizational AGI/ASI Governance, Architecture, Safety, and Implementation Blueprint</title>
<abstract>
This report provides an implementation-ready blueprint for Fortune 500, Global 2000, and G‑SIFI institutions and supervisors from 2026 to 2030. It unifies enterprise AI governance, regulatory compliance engineering, high-assurance platform architecture, AGI/ASI safety and containment, civilizational compute governance, and financial-services model risk controls. It includes dependency-aware rollout planning, machine-readable governance artifacts (JSON/YAML/Rego), and regulator-ready sections for boards, C-suites, architects, platform engineers, and AI safety teams.
</abstract>
<content>

## 1) Scope, Audience, and Design Principles
- **Audience:** Board risk committees, C-suites, regulators, model risk teams, enterprise architects, AI platform engineers, and AI safety researchers.
- **Institutional scope:** Multi-jurisdiction enterprises spanning US/EU/UK/APAC with prudential and conduct exposure.
- **Design principles:** legality-by-design, safety-by-design, controls-as-code, evidence-by-default, and independent challenge for all high-impact AI.

## 2) Integrated Regulatory Compliance Framework Mapping and Implementation

### 2.1 Control ontology and traceability model
Adopt a canonical enterprise control model (`AIGOV-*`) with immutable trace links:
1. legal/supervisory source,
2. control objective,
3. implementation control,
4. test procedure,
5. evidence artifact,
6. accountable owner.

### 2.2 Framework crosswalk (required coverage)
- **EU AI Act + Annex IV:** risk classification, provider/deployer obligations, conformity pathways, technical documentation and post-market monitoring.
- **NIST AI RMF 1.0:** Govern/Map/Measure/Manage aligned to risk lifecycle and operating KPIs/KRIs.
- **NIST AI 600-1:** secure/trustworthy AI engineering controls, adversarial robustness, and resilience.
- **ISO/IEC 42001:** AI management system (AIMS), audit cycle, continual improvement.
- **OECD AI Principles:** transparency, robustness, accountability, and human-centered outcomes.
- **GDPR Article 22:** safeguards for significant automated decisions (human review, contestability, meaningful information).
- **FCRA/ECOA:** adverse action reasoning and anti-discrimination controls in credit decisions.
- **Basel III/IV + SR 11-7:** model risk governance, prudential oversight, overlays, and board reporting.
- **NIS2:** cyber resilience, AI dependency security, incident reporting and supply-chain control.
- **FCA Consumer Duty + SMCR:** customer outcomes governance and explicit senior-manager accountability.
- **MAS/HKMA FEAT:** fairness, ethics, accountability, and transparency control packs for APAC.

### 2.3 Compliance implementation pattern (enterprise)
- **Policy layer:** legal interpretation + control text + jurisdiction overlays.
- **Enforcement layer:** OPA/Rego admission and runtime policies.
- **Evidence layer:** Kafka event streams + WORM retention + legal hold.
- **Assurance layer:** independent validation, 2LOD challenge, 3LOD audit, external assurance.
- **Regulatory layer:** jurisdiction-ready supervisory evidence packs and notification workflows.

## 3) Institutional-Grade Governance Platform Technical Architecture

### 3.1 Capability domains
- **Sentinel AI Governance Platform v2.4** (policy registry, tiering, approvals, exceptions, evidence graph).
- **WorkflowAI Pro** (HITL orchestration, approvals, overrides, and accountability trails).
- **EAIP** (model gateway, policy mediation, secure tool-use brokering, and failover routing).
- **High-assurance RAG** (source provenance, trust scoring, citation constraints, and retrieval-integrity checks).

### 3.2 Control stack specification
- **Kubernetes/Kafka/OPA:** policy admission, runtime guardrails, immutable telemetry.
- **Docker Swarm hardening:** mTLS everywhere, signed-image-only deployment, scoped secrets, node attestation.
- **Node.js/Python governance sidecars:** mandatory evidence envelope for every inference/action.
- **Next.js explainability UX:** rationale views, recourse process, policy provenance and model card surfacing.
- **Terraform/CI/CD governance automation:** policy test gates, SoD approvals, provenance attestations, rollback controls.

### 3.3 Hyperparameter and drift standards
- **Parameter governance:** approved envelope per model tier; material-change classification.
- **Drift standards:** data/concept/behavior/policy drift metrics with mandatory response triggers.
- **Model update protocol:** major updates require revalidation + compliance sign-off before promotion.

## 4) AGI/ASI Safety, Containment, and Crisis Simulation Blueprint

### 4.1 Safety framework integration
- **Luminous Engine Codex:** safety claims catalog and evidentiary burden framework.
- **Cognitive Resonance Protocol:** coherence/deception stress testing and emergent behavior diagnostics.
- **Sentinel / Omni-Sentinel:** enterprise monitoring and emergency intervention plane.

### 4.2 Containment architecture for frontier systems
- isolated AGI containment labs,
- hardened egress and tool controls,
- dual-key authorization for external effects,
- autonomous behavior tripwires,
- immediate kill/quarantine pathways.

### 4.3 Frontier risk taxonomy
- misuse acceleration,
- cyber offense amplification,
- financial market manipulation,
- institutional deception/persuasion,
- recursive capability escalation.

### 4.4 Crisis simulation standard
- quarterly tabletop and semiannual live simulation,
- regulator-observer scenarios for Tier 4/5,
- mean-time-to-containment and incident quality KPIs,
- postmortem evidence and control remediation SLAs.

## 5) Civilizational-Scale AI and Compute Governance Mechanisms

### 5.1 Global governance construct
- **International Compute Governance Consortium (ICGC)**
- **Global Compute Registry**
- **Treaty-aligned systemic governance forum**

### 5.2 Mechanism registry
- **GACRA, GASO, GFMCF, GAICS, GAIVS, GACP, GATI, GACMO, FTEWS, GAI-SOC, GAIGA, GACRLS, GFCO, GAID, GASCF**

### 5.3 Enterprise obligations
- register above-threshold compute,
- disclose severe incidents and near misses,
- participate in cross-border simulations,
- maintain schema interoperability for audit and crisis coordination.

## 6) Financial Services-Specific Model Risk and Governance

### 6.1 Credit and lending
- adverse action explainability,
- protected-group fairness monitoring,
- recourse and manual escalation controls.

### 6.2 Trading and market support
- no fully autonomous high-impact execution,
- stress/reverse-stress controls,
- real-time supervisory kill-switch authority.

### 6.3 Enterprise risk and fiduciary advisors
- suitability and fiduciary constraints,
- systemic spillover pre-checks,
- liquidity and contagion scenario gates.

### 6.4 SR 11-7 lifecycle integration
inventory -> tiering -> validation -> challenge -> production monitoring -> periodic revalidation -> retirement.

## 7) 2026–2030 Dependency-Aware Implementation Roadmap

### Phase A (2026): Baseline controls and legal-compliance anchoring
Dependencies: inventory + tiering + policy baseline + evidence stream bootstrap.

### Phase B (2027): Automation and operating scale
Dependencies: standardized sidecar telemetry + release gates + multi-jurisdiction packs.

### Phase C (2028): Frontier assurance and resilience
Dependencies: containment lab maturity + crisis simulations + external assurance.

### Phase D (2029): Systemic-risk integration
Dependencies: compute registry linkage + mechanism interoperability + systemic exercises.

### Phase E (2030): Adaptive governance and treaty-compatible operations
Dependencies: dynamic control tuning + supervisory data exchange maturity + continuous assurance.

## 8) Regulator-Ready Report Sections by Stakeholder
<section audience="board">
- risk appetite posture,
- concentration exposure,
- unresolved exceptions,
- investment and capability roadmap.
</section>

<section audience="c_suite">
- accountability model,
- operational KRIs/KPIs,
- cross-border compliance heatmap,
- strategic deployment constraints.
</section>

<section audience="regulator">
- control mapping and legal traceability,
- test evidence and exceptions,
- incidents/remediation,
- forward risk treatment plan.
</section>

<section audience="enterprise_architects">
- reference architecture,
- system boundaries and trust zones,
- dependency and resilience design,
- control integration points.
</section>

<section audience="ai_platform_engineers">
- runtime enforcement policies,
- release gate definitions,
- observability/evidence contracts,
- rollback and incident hooks.
</section>

<section audience="ai_safety_researchers">
- capability evaluations,
- containment efficacy,
- deceptive-behavior and misuse testing,
- residual risk and open research queue.
</section>

## 9) Machine-Readable Governance Artifacts
- `governance_blueprint/compliance_profile_2026.json`
- `governance_blueprint/civilizational_compute_governance_framework.yaml`
- `governance_blueprint/opa/systemic_risk_guardrails.rego`
- `governance_blueprint/annex_iv_technical_documentation_template.json`
- `governance_blueprint/rollout_plan_2026_2030.yaml`

</content>
Original file line number Diff line number Diff line change
@@ -0,0 +1,30 @@
{
"template_id": "eu-ai-act-annex-iv-tech-doc-v1",
"version": "1.0.0",
"sections": [
{"id": "A", "name": "General system description", "required": true},
{"id": "B", "name": "Design and development specifications", "required": true},
{"id": "C", "name": "Data requirements and governance", "required": true},
{"id": "D", "name": "Risk management system", "required": true},
{"id": "E", "name": "Post-market monitoring", "required": true},
{"id": "F", "name": "Human oversight measures", "required": true},
{"id": "G", "name": "Performance and limitations", "required": true},
{"id": "H", "name": "Cybersecurity and resilience", "required": true}
],
"metadata": {
"provider": "",
"deployer": "",
"model_id": "",
"model_version": "",
"intended_purpose": "",
"risk_classification": "",
"jurisdictions": [],
"responsible_executive": ""
},
"evidence_links": {
"validation_report": "",
"data_lineage_record": "",
"monitoring_dashboard": "",
"incident_playbook": ""
}
}
27 changes: 18 additions & 9 deletions governance_blueprint/artifact_manifest.json
Original file line number Diff line number Diff line change
@@ -1,18 +1,27 @@
{
"package": "enterprise_agi_asi_governance_blueprint",
"version": "1.3.1",
"generated_utc": "2026-04-27T06:11:04Z",
"version": "1.4.5",
"generated_utc": "2026-04-28T02:47:09Z",
"artifacts": {
"control_mapping_matrix.csv": "8af4170e62e6aec3c12f3f554d29fe31e6c59c196cd9b3e1590f1238597ce228",
"evidence_event_schema.json": "7c84f8fce1cefeff08308a2763c086eb4ede05881881cd53c484e879df04196a",
"opa/release_gate.rego": "bd117bddd2c77a0fd5cc4741aa6805b6f1f711d2baa5732ca037ea4db7b60c43",
"compliance_profile_2026.json": "aa3468812b58f05095d6d96e7def2262c90c142dadf13bf91bc8423a85ae345f",
"annex_iv_technical_documentation_template.json": "08c791484963dd46e0cbc0e76358229813816f66d050df4e9783e73ded7e787e",
"civilizational_compute_governance_framework.yaml": "15a2b94042bcd6f79643be6289febbef3b697f29424e842b76ee8944027d9d27",
"roadmap_2026_2030.yaml": "35132b486b360d91ceab94e7949278c755a28dbab0cccf64e0b3a776d7dab485",
"validation/validate_artifacts.py": "0908bb44ecf2b209861fb3fe0259bad2b652d94b1f6c50c45592b074f52848e0",
"validation/selftest_validate_artifacts.py": "50414aa4ecf39166268d76ab0363ad2ec9ac32cde6b27ae5c631764fd7bce29b",
"validation/generate_artifact_manifest.py": "654479289df4a57ab58288adcbb5c9e23861f3b3a6e4d524b8214bb8c992d060",
"validation/run_validation_suite.py": "4c7038c4d3da1d6fb3f4c43bddd5b2237856b90bd568a17d03a1d16cfc904781",
"validation/selftest_run_validation_suite.py": "2f987933769c0530eaa7ad51a0454781e8bd90bb700c120219dae5a96645adbe",
"rollout_plan_2026_2030.yaml": "2d735de1f810f23828f9798154ac5dfe50460b4e583909ea8b677dfeafb26061",
"opa/release_gate.rego": "3a8b5e3a4c90e78bfd5f9dee1f4ca4927d198238aa18679e4a78aa94623d453c",
"opa/systemic_risk_guardrails.rego": "5eb9d5f7061aa0f03194d505c8eb3347cbac00138ff3ce28ec1b71bee5382ab7",
"validation/validate_artifacts.py": "a82ba842ada8a22d3d8cd37553b4c71691ec2da32f6add3c18a7baa9b0cbc1a7",
"validation/generate_artifact_manifest.py": "528970f9f6e35a0c50fd97c0551cc9230b2c7ce967f7b590a2dea2821d19c41c",
"validation/run_validation_suite.py": "2e00f22a83e572424b07ba9f6984394c8b99d2317fb40134fd2dd97d6708a2b6",
"validation/lint_python_sources.py": "52b36b1427679624fd9778dc93cb7b318b4c882930e78c0947a37d5185dafae9",
"validation/validate_dashboard_links.py": "e854e2c61ac6e31f880fce8e28c6ed95856d13a85fdfdbcf124df74925b1461a"
"validation/validate_dashboard_links.py": "e854e2c61ac6e31f880fce8e28c6ed95856d13a85fdfdbcf124df74925b1461a",
"validation/selftest_generate_artifact_manifest.py": "381af02a7b337e11af7df7992012736a5ec9a37b1009c8aa3e918ad589baa8d2",
"validation/selftest_run_validation_suite.py": "697fdd88db942deb2a4d4f5cb17cabd5c36ce4278e7c6e70c9059c97fa1f47c1",
"validation/selftest_validate_artifacts.py": "84e95dfe25db9586c1806fda0fba1f4e8bb10b6c02360a224b12cddb7d82c06c"
},
"external_artifacts": {
"REGULATOR_READY_AGI_ASI_TECHNICAL_REPORT_2026_2030.md": "b590161a765704a9d320dcfa1fae2f8285bc816fc56cf25062e11c3f27bcdbee"
}
}
Original file line number Diff line number Diff line change
@@ -0,0 +1,58 @@
framework_id: civilizational-compute-governance-2030
version: 1.0.0
updated_at: 2026-04-27T00:00:00Z
institutions:
- International Compute Governance Consortium (ICGC)
- Global Compute Registry
- Treaty-Aligned Systemic Risk Governance Forum
mechanisms:
GACRA:
name: Global AI Compute Registration Authority
purpose: Register frontier compute assets and cross-border usage declarations.
GASO:
name: Global AI Safety Observatory
purpose: Consolidate safety incidents and near misses.
GFMCF:
name: Global Frontier Model Certification Framework
purpose: Maintain safety certification baseline for frontier systems.
GAICS:
name: Global AI Incident Coordination System
purpose: Coordinate transnational containment and response.
GAIVS:
name: Global AI Verification Standard
purpose: Define verifiable claims, evaluations, and evidence schemas.
GACP:
name: Global Algorithmic Containment Protocol
purpose: Standardize emergency containment actions.
GATI:
name: Global AI Treaty Interface
purpose: Technical interoperability layer for treaty reporting.
GACMO:
name: Global AI Capacity Monitoring Office
purpose: Monitor concentration and capacity risk in advanced compute supply.
FTEWS:
name: Frontier Threat Early Warning System
purpose: Generate cross-sector alerts for escalatory AI threats.
GAI-SOC:
name: Global AI Security Operations Center
purpose: Operate shared detection and response telemetry for severe events.
GAIGA:
name: Global AI Governance Interoperability Gateway
purpose: Bridge institution-level governance data with regulator systems.
GACRLS:
name: Global AI Compute Resource Licensing System
purpose: License high-threshold compute access by risk class.
GFCO:
name: Global Frontier Compute Observatory
purpose: Assess trends in frontier training and inference capacity.
GAID:
name: Global AI Disclosure Standard
purpose: Normalize disclosures for capability, risk, and incidents.
GASCF:
name: Global AI Systemic Containment Facility
purpose: Federated contingency coordination for systemic AI crises.
enterprise_obligations:
- Register above-threshold compute clusters and material upgrades.
- Provide machine-readable incident disclosures within jurisdictional deadlines.
- Participate in annual cross-border crisis simulations.
- Maintain compatibility with shared verification and disclosure schemas.
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