# AI Privacy
> [!metadata]- Metadata
> **Published:** [[2025-02-09|Feb 09, 2025]]
> **Tags:** #🌐 #learning-in-public #artificial-intelligence #cognitive-science #ethical-ai#bias-mitigation
Privacy in AI systems involves protecting sensitive information while maintaining model utility. It encompasses data protection, consent management, and balancing individual rights with system performance.
## Key Privacy Concerns
1. **Data Collection**:
- Informed consent requirements
- Data minimization principles
- Purpose limitation
- Storage constraints
2. **Model Training**:
- Protection of training data
- Prevention of data leakage
- [[Fairness Definitions|Fair representation]]
- Secure computation
3. **Inference Privacy**:
- Protection of user queries
- Secure model outputs
- Prevention of model inversion attacks
- Membership inference protection
## Privacy-Preserving Techniques
1. **Differential Privacy**:
- Mathematical privacy guarantees
- Noise addition methods
- Privacy budget management
- Trade-off with utility
2. **Federated Learning**:
- Distributed model training
- Local data processing
- Aggregation without raw data sharing
- Cross-silo collaboration
3. **Encryption Methods**:
- Homomorphic encryption
- Secure multi-party computation
- Zero-knowledge proofs
- Privacy-preserving protocols
## Implementation Challenges
1. **Technical Constraints**:
- Computational overhead
- Performance impact
- Integration complexity
- Scalability issues
2. **Regulatory Compliance**:
- GDPR requirements
- CCPA compliance
- Industry-specific regulations
- International standards
## Relationship to Ethical AI
Privacy protection supports:
- [[Algorithmic Bias|Bias prevention]]
- [[Fairness Definitions|Fair treatment]]
- Individual autonomy
- Trust in AI systems
## Best Practices
1. **Data Governance**:
- Clear privacy policies
- Data handling procedures
- Access controls
- Audit mechanisms
2. **User Rights**:
- Right to explanation
- Data access rights
- Right to be forgotten
- Consent management
[Learn more about privacy in AI systems](@https://pmc.ncbi.nlm.nih.gov/articles/PMC10132017/)