Standards Alignment
Reality Fidelity implements core requirements from leading AI governance standards and frameworks.
Standards Landscape
Multiple standards bodies have developed frameworks for AI governance. While they differ in scope and specificity, they share common themes that Reality Fidelity directly addresses:
- Risk-based approach to AI system management
- Documentation and traceability requirements
- Human oversight and intervention capabilities
- Continuous monitoring and improvement
- Transparency and explainability
ISO/IEC 42001 — AI Management System
The first international standard for AI management systems, providing a framework for organizations to establish, implement, and maintain responsible AI practices.
Key Requirements Addressed by Reality Fidelity:
- Risk Assessment (6.1) — Completeness gates implement risk controls at critical decision points
- AI System Lifecycle (7.2) — Provenance tracking documents system behavior throughout lifecycle
- Data Quality (7.3) — Required state verification ensures input data quality
- Monitoring (9.1) — Audit trails enable continuous monitoring of AI outputs
NIST AI Risk Management Framework
Voluntary U.S. framework organized around four core functions: Govern, Map, Measure, and Manage.
Reality Fidelity Alignment:
| NIST Function | Reality Fidelity Implementation |
|---|---|
| Govern | Required state registries define governance policies |
| Map | Authoritative output classification identifies risks |
| Measure | Completeness gates quantify missing state |
| Manage | Gates prevent outputs when requirements unmet |
IEEE Standards for AI
IEEE has developed multiple standards addressing AI ethics, transparency, and governance.
Relevant Standards:
- IEEE 7000 — Model Process for Addressing Ethical Concerns
- IEEE 7001 — Transparency of Autonomous Systems
- IEEE 7002 — Data Privacy Process
- IEEE 7010 — Wellbeing Metrics for AI
Reality Fidelity's provenance tracking and audit trails directly support IEEE transparency and documentation requirements.
ISO/IEC 23894 — AI Risk Management
Guidance on managing risk specifically for AI systems, complementing general risk management standards.
Key Alignments:
- Risk identification through authoritative output classification
- Risk analysis via required state completeness assessment
- Risk treatment through completeness gate implementation
- Risk monitoring via continuous audit trail analysis
Cross-Standard Alignment Matrix
| Requirement Theme | ISO 42001 | NIST AI RMF | IEEE | Reality Fidelity |
|---|---|---|---|---|
| Risk Management | ✓ | ✓ | ✓ | Completeness Gates |
| Documentation | ✓ | ✓ | ✓ | Audit Trails |
| Traceability | ✓ | ✓ | ✓ | Provenance Tracking |
| Human Oversight | ✓ | ✓ | ✓ | Required State: Oversight |
| Data Quality | ✓ | ✓ | ✓ | Input Completeness |
Certification Support
Reality Fidelity provides documentation and controls that support certification against:
- ISO/IEC 42001 AI Management System certification
- SOC 2 Type II for AI systems
- Industry-specific certifications (HITRUST for healthcare, PCI DSS for payments)