Compliance
AI Compliance and Regulation
Major AI Regulations
EU AI Act (2024)
The most comprehensive AI regulation globally:
| Risk Level | Requirements | Examples |
|---|---|---|
| Unacceptable | Banned | Social scoring, real-time biometric ID |
| High-risk | Strict obligations | Medical devices, credit scoring, hiring |
| Limited risk | Transparency | Chatbots, emotion detection |
| Minimal risk | No requirements | Spam filters, games |
US Regulations
- Executive Order on AI (Oct 2023): Safety, security, privacy
- State laws: California, Colorado AI governance bills
- Sector-specific: FDA for medical AI, SEC for financial AI
Other Regions
- China: Generative AI regulations, algorithm registration
- UK: Pro-innovation framework with sector guidance
- Canada: AIDA (Artificial Intelligence and Data Act)
Compliance Requirements for High-Risk AI
Documentation
- Technical documentation of system
- Training data documentation
- Risk assessment and mitigation
Quality Management
- Conformity assessment procedures
- Data governance practices
- Post-market monitoring
Transparency
- Clear AI disclosure to users
- Explainability of decisions
- Human oversight mechanisms
Industry Standards
| Standard | Scope | Status |
|----------|-------|--------|
| ISO/IEC 42001 | AI management systems | Published 2023 |
| IEEE 7000 | Ethics in system design | Published |
| NIST AI RMF | Risk management | Published 2023 |
Practical Compliance Steps
1. Inventory: Document all AI systems and their uses
2. Classify: Determine risk level for each system
3. Gap analysis: Compare current practices to requirements
4. Remediate: Implement required controls
5. Monitor: Ongoing compliance and audit readiness
LLM-Specific Considerations
- Copyright and training data provenance
- Generated content attribution
- Misinformation and harm potential
- Cross-border data flows for API calls