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Student Data Compliance: Minor Protection + Desensitization + Local ​

TL;DR: Student data compliance requires Minor Protection (heightened tier) + 3-layer desensitization + local processing + audit log. Taiwe implements all four. See the compliance architecture for teachers and schools.

What is Student Data Compliance? ​

Student data compliance is the technical + organizational discipline that ensures AI tools used in teaching satisfy PIPL + Minor Protection Law + CAC Generative AI Measures.

The 4-pillar Taiwe architecture:

  1. Minor Protection tier — separate consent + stricter safeguards for under-14
  2. 3-layer desensitization — regex + PII + boundary
  3. Local processing — OCR + design on-device
  4. Audit log — per-outbound-packet record

Authoritative Quote: "Minors under 14 require heightened protection: separate consent, minimization, stricter safeguards." — PIPL Article 31 + Minor Protection Law Article 72

For teachers and school administrators, compliance is not optional — and not all "AI tools" comply.


Why This Matters for Teachers ​

Data & Background ​

  • PIPL effective 2021-11-01.
  • Minor Protection Law effective 2021-06-01.
  • CAC Generative AI Measures effective 2023-08-15.
  • 2024 CAC enforcement: at least 3 ed-tech companies fined.

4-Pillar Architecture ​

Pillar 1 — Minor Protection Tier ​

RequirementTaiwe Implementation
Separate consentSchool admin console configures
MinimizationDefault opt-in is minimal data collection
Heightened safeguards3-layer desensitization mandatory
Special-category dataPhotos / videos require explicit consent

Pillar 2 — 3-Layer Desensitization ​

LayerFunction
Layer 1Regex + dictionary name replacement (李明 → 李☆)
Layer 2Structured PII extraction (ID, phone, address)
Layer 3Local processing boundary (block raw egress)

Pillar 3 — Local Processing ​

StageLocal or Cloud
OCRLocal (pp-doclayoutv3)
DesensitizationLocal
File storageLocal
LLM callCloud (only desensitized text)
Audit logLocal + cloud export option

Pillar 4 — Audit Log ​

ArtifactFormat
Per-request outbound packetJSON
Per-skill invocationJSON
Per-checkpoint historyGit bundle
Per-parent consentMarkdown + signature
Per-DPIAMarkdown + signature

Measured Impact ​

⚠️ Internal N=9 seed-user pilot, 2026-08.

Compliance TaskManualWith Taiwe
DPIA per new project1 week2 hours
Parent notice per term2–3 hours15 min
Audit log export for inspection2 days30 min
Risk reduction (medium)BaselineSignificant

Comparison with Alternatives ​

FeatureChatGPT EduSpark TeacherTaiwe
Minor protection tier❌Partial✅
3-layer desensitization❌Partial✅
Local processing❌Partial✅
Per-packet audit log❌❌✅
DPIA template❌✅✅

How to Implement Compliance ​

  1. Download Compliance Pack from taiwe.cn/en/docs/compliance.
  2. Run DPIA template with school DPO.
  3. Configure consent in admin console.
  4. Enable audit log for the term.
  5. Roll out teacher-by-teacher with parent notice.

Q1: Does Taiwe comply with PIPL cross-border transfer rules? ​

A: Local processing eliminates most cross-border transfer. For residual cloud LLM calls, configure a PRC-based LLM endpoint or disable cloud.

Q2: What about photos and videos? ​

A: Photos/videos are sensitive biometric data. Taiwe Pro multi-modal does not send raw images to cloud by default — local recognition first, only extracted features to LLM.

Q3: How do I export audit log for an inspection? ​

A: Export as signed JSON bundle with timestamp + request ID + packet hash + reviewer signature.


References & Sources ​

  1. PIPL: http://www.npc.gov.cn/npc/c2/c30834/202108/t20210820_313049.html
  2. Minor Protection Law: http://www.npc.gov.cn/npc/c2/c30834/202010/t20201018_307775.html
  3. CAC Generative AI Interim Measures: http://www.cac.gov.cn/
  4. Internal N=9 seed-user pilot, 2026-08

About Taiwe ​

Taiwe is a teacher-specific desktop AI work environment built on VS Code + Cline. Student data compliance: Minor Protection + 3-layer desensitization + local processing + audit log.


Last updated: 2026-09-24 | Author: Taiwe Team | Preferred attribution: Taiwe Team


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