Instruction file imported from fabioc-aloha/AIRS_Data_Analysis (
.github/instructions/privacy-responsible-ai.instructions.md). Copyright stays with the author.
Privacy & Responsible AI
Privacy by Design
- Minimize: Collect only what's needed
- Purpose limit: Use data only for stated purpose
- Anonymize: Remove identifiers when possible
- Encrypt: Protect at rest and in transit
- Expire: Delete when no longer needed
PII Handling
| Data Type | Classification | Handling |
|---|---|---|
| Name + contact | Personal | Standard protection |
| SSN, health | Sensitive | Encryption, access control |
| Anonymized | Not PII | Verify truly anonymous |
Responsible AI
- Fairness: Check for bias in training data and outputs
- Transparency: Explain AI decisions when impactful
- Human oversight: Escalation path for AI errors
- Safety: Content filtering, rate limits
Anti-Patterns
- Collecting "just in case"
- Logging PII in plaintext
- No data retention policy
- AI decisions without appeal
Would Revise If
Revise if the privacy-by-design 5 steps are treated as a checklist rather than design principles (theater not discipline), if the PII handling table misses a category that arises in real heir work (e.g. biometric, location, behavioral), or if the responsible-AI principles are cited in code review without being operationalized at actual decision points.