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ai-privacy-impact-template

ai-privacy-impact-template

github.com/mukul975Security32343 installsUpdated 32w ago
Repository

About ai-privacy-impact-template

A combined GDPR DPIA and AI Act conformity assessment template for teams evaluating high-risk AI systems. It brings both frameworks into a shared risk score, mitigation plan, and documentation structure.

Key features

  1. 01Combine GDPR DPIA and AI Act assessment
  2. 02Provide a weighted risk-scoring matrix
  3. 03Map requirements across both regulations
  4. 04List technical and organisational mitigations
  5. 05Cover monitoring, records, and quality management

Use cases

  1. 01Assess a high-risk AI system under both frameworks
  2. 02Consolidate privacy and fundamental-rights risks
  3. 03Prepare compliance measures and assessment documentation

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/mukul975/privacy-data-protection-skills --skill ai-privacy-impact-template

After installing, type/ai-privacy-impact-templatein Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

assets/
template.md
references/
standards.md
workflows.md
scripts/
process.py

Details

From the project README

Combined DPIA and AI Act Conformity Assessment Template

Overview

High-risk AI systems under the EU AI Act must undergo both a GDPR Art. 35 DPIA and an AI Act conformity assessment. Rather than conducting these as separate exercises, this skill provides an integrated template that satisfies both frameworks simultaneously. The combined assessment ensures consistency between GDPR privacy risk analysis and AI Act safety and fundamental rights evaluation, reduces duplication, and provides a single risk scoring matrix covering both regulatory dimensions. Art. 26(9) AI Act explicitly requires deployers to use DPIA results when fulfilling AI Act obligations.

Combined Risk Scoring Matrix

Risk Dimensions
DimensionSourceWeight
Privacy risk to data subjectsGDPR Art. 35(7)(c)30%
Fundamental rights impactEU AI Act Art. 9(2)(a)25%
Accuracy and reliability riskEU AI Act Art. 1520%
Transparency and explainability gapGDPR Art. 13(2)(f) + AI Act Art. 1315%
Human oversight adequacyGDPR Art. 22 + AI Act Art. 1410%
Scoring Scale (Per Dimension)
ScoreLevelDescription
1MinimalRisk negligible; controls effective
2LowMinor risk; standard controls sufficient
3MediumModerate risk; enhanced controls needed
4HighSignificant risk; intensive mitigation required
5CriticalSevere risk; may require processing suspension
Overall Risk Classification
Weighted ScoreClassificationAction Required
1.0-1.5LowStandard monitoring
1.6-2.5MediumEnhanced monitoring and periodic review
2.6-3.5HighActive mitigation and DPO/Board oversight
3.6-4.5Very HighArt. 36 prior consultation; deployment hold pending mitigation
4.6-5.0CriticalDo not deploy; fundamental redesign required

GDPR DPIA Requirements (Art. 35(7))

ElementReferenceCombined Assessment Section
Systematic description of processingArt. 35(7)(a)Section 2: AI System Description
Necessity and proportionalityArt. 35(7)(b)Section 3: Necessity Assessment
Risk assessmentArt. 35(7)(c)Section 5: Combined Risk Register
Mitigation measuresArt. 35(7)(d)Section 6: Mitigation Measures

AI Act Conformity Assessment Requirements

For high-risk AI systems (Annex III), the conformity assessment per Art. 43 requires:

ElementReferenceCombined Assessment Section
Risk management systemArt. 9Section 5: Combined Risk Register
Data governanceArt. 10Section 2: Training Data Governance
Technical documentationArt. 11Full combined assessment document
Record-keepingArt. 12Section 7: Monitoring and Logging
TransparencyArt. 13Section 4: Transparency Assessment
Human oversightArt. 14Section 4: Human Oversight
Accuracy, robustness, cybersecurityArt. 15Section 5: Technical Risk Assessment
Quality management systemArt. 17Section 8: Quality Management

Mitigation Measures Framework

Technical Measures
MeasureGDPR RelevanceAI Act RelevancePriority
Differential privacyTraining data protectionRobustness (Art. 15)High for sensitive data
Model output perturbationModel inversion protectionAccuracy trade-off (Art. 15)Medium
Fairness constraintsNon-discrimination (Art. 5(1)(a))Bias prevention (Art. 10)High for high-risk
Explainability tools (SHAP/LIME)Art. 13(2)(f) logic explanationInterpretability (Art. 13)High
Input/output PII filteringData minimisation (Art. 5(1)(c))Accuracy (Art. 15)High for generative AI
Encryption (rest/transit)Security (Art. 32)Cybersecurity (Art. 15)Standard
Access controls (RBAC)Security (Art. 32)Cybersecurity (Art. 15)Standard
Anomaly detectionBreach detection (Art. 33)Robustness (Art. 15)Medium
Organisational Measures
MeasureGDPR RelevanceAI Act Relevance
AI ethics review boardAccountability (Art. 5(2))Quality management (Art. 17)
Model cardsTransparency (Art. 13-14)Technical documentation (Art. 11)
Regular bias auditsFairness (Art. 5(1)(a))Bias monitoring (Art. 10)
Incident response for AIBreach notification (Art. 33-34)Post-market monitoring (Art. 72)
Staff training on AI risksAccountabilityHuman oversight (Art. 14)
Documentation and record-keepingAccountability (Art. 5(2))Record-keeping (Art. 12)

Enforcement Relevance

  • AI Act Art. 26(9): Deployers of high-risk AI shall use GDPR Art. 35 DPIA information when fulfilling AI Act obligations — the combined assessment implements this requirement.
  • AI Act Art. 43: Conformity assessment procedures for high-risk AI systems.
  • GDPR Art. 35: DPIA requirements — the combined template satisfies all Art. 35(7) elements.

Integration Points

  • ai-dpia: Combined template extends the AI DPIA methodology
  • ai-act-high-risk-docs: Conformity assessment documentation aligns with high-risk requirements
  • ai-bias-special-category: Bias assessment results feed into combined risk register
  • ai-automated-decisions: Human oversight assessment integrates Art. 22 and Art. 14 requirements

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