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