Governance & Compliance · Data artifact
DPIA Record
Data artifactGovernance & ComplianceSafety, Security & Governancearc:DPIARecord
A living Data Protection Impact Assessment recording identified risks with harm pathways, data-flow mapping, mitigations, stakeholder impact, necessity and proportionality justification, residual risk and an approval decision.
Responsibility. Documents and governs high-risk personal-data processing risks before and during deployment.
Also known as: Data Protection Impact Assessment, Privacy impact assessment
Relationships
Design guidance
- MUST be completed before large-scale processing, automated decisions with legal or significant effects, sensitive-category processing, novel technology or consequential AI/ML decisions.
- MUST be revised when new data sources are added or model capabilities expand.
- SHOULD be reviewed by others and conclude proceed, proceed with mitigation, or redesign (Ref9.05).
- SHOULD test whether purposes could be achieved with less data, e.g., pseudonymized claim IDs instead of names.
Classification
- Patterns
- Privacy by design
- Quality attributes
- Transparency and accountability (NIST AI RMF: accountable and transparent)
- Risks mitigated
- Unauthorized disclosure of sensitive dataAlgorithmic bias producing disparate denial ratesIndividuals unable to understand or challenge automated decisionsExternal attacks on valuable data
- Frameworks & regulations
- GDPR Art. 35EU AI Act (high-risk requirements)
Sources
- Ch9.7: T. Nguyen, "GDPR and Data Protection Regulations," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 9.7. ISBN: 9798244538229.
- Ref9.03: "Regulatory Compliance Frameworks for AI Systems," unpublished reference note (references/Chapter 9 - Safety, Ethics, and Compliance/03-Regulatory-Compliance-Frameworks.md), Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam supplementary materials, 2026. unpublished note
- Ref9.05: "Privacy and Data Protection for AI Systems," unpublished reference note (references/Chapter 9 - Safety, Ethics, and Compliance/05-Privacy-Data-Protection.md), Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam supplementary materials, 2026. unpublished note