Healthcare privacy & erasure
P11.applied-llm-systems.04 · Audience: guest, it-ml, language-pro · Prerequisites: Applied LLMOps
Running the search + assistant under GDPR for health data: it is Art. 9 special-category data, so processing is prohibited unless a specific condition applies. Draw the line before the model, and when a right-to-erasure request arrives, propagate the delete to every derived copy. (Cross-refs: P13 MLOps, P16 Governance.)
Ordinary personal data follows GDPR's general rules. Health data — and anything from which health can be inferred — is special-category under Article 9, which prohibits processing unless a specific condition applies (explicit consent, or health/social-care provision).
| Concept | What it means here |
|---|---|
| Special category (Art. 9) | symptoms, conditions, a cardiology booking — process only under an Art. 9 condition |
| Lawful basis | explicit consent, or health/social-care provision — documented |
| EU data residency | a third-party LLM API call can be a cross-border transfer needing safeguards |
| Inference risk | even a search query (“Spanish-speaking oncologist”) can reveal a condition |
⚠️ A symptom typed into a search box is health data — including in logs, caches, and anything sent to a model provider.
⚡ Interview Ref — the quick-scan Reference face
- Art. 9: health data (and anything health-inferring) is special-category — processing prohibited without a condition (explicit consent / health-care provision). A search query can reveal a condition.
- Before the model: PII-before-LLM boundary; prompts/logs/caches are not safe stores; vendor API = new processor + cross-border; purpose limitation (no silent reuse for training).
- Privacy-by-design + DPIA: minimization/pseudonymization/access control built in; DPIA required for high-risk special-category processing.
- Right to erasure: propagate outward — source → embeddings → ANN index → caches → logs → trained weights (hard, only approximable).
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