ai-data-subject-rights
Installation
SKILL.md
Data Subject Rights for AI Systems
Overview
AI systems create unique challenges for data subject rights exercise. Traditional rights mechanisms designed for structured databases do not map directly to ML model architectures where personal data is encoded in model weights, reproduced in model outputs, or used in opaque decision processes. This skill provides the framework for implementing each GDPR right (Arts. 15-22) and the AI Act Art. 86 right to explanation in the context of AI processing, addressing both training-time and inference-time rights.
Rights Framework for AI
Right of Access (Art. 15)
| AI Context | Obligation | Implementation |
|---|---|---|
| Training data contribution | Confirm whether data subject's data was in training set; provide copy if feasible | Training data catalogue indexed by data subject identifier; membership query |
| AI inference inputs | Provide data used as input to AI decision | Log inference inputs with data subject linkage |
| AI inference outputs | Provide AI decision/score/classification affecting data subject | Decision logging with data subject ID |
| Logic explanation | Art. 15(1)(h): meaningful information about logic of automated decisions | SHAP/LIME explanation on request or system-level explanation |
| Training data source | Art. 14(2)(f): source of data if not collected from data subject | Training data provenance documentation |
Technical Challenges:
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