By sector · Education and training
Education is named as a high-risk area in several instruments: admissions, assessment, proctoring and the allocation of learning are decisions about people, often minors. Institutions are deployers; edtech vendors are providers; the duties on both are listed here with the controls that meet them.
Data-protection law and AI law both treat children as needing stronger safeguards. Notices have to be understood by the people receiving them, oversight has to be real, and emotion recognition and some biometric uses are prohibited outright in some jurisdictions.
Most educational AI is bought, so the contract and the vendor's documentation are the institution's first evidence. The contractual and vendor controls below carry that.
Sorted by how many of the duties on this page each control satisfies, so the ones worth building first are at the top. A control page lists every other duty it serves, in every jurisdiction.
| Control | Satisfies | Supports | Owner · frequency |
|---|---|---|---|
| Decision explanation, human review and appeal route Process | 3 | 1 | Customer operations lead · once per ai system |
| AI risk assessment and lifecycle risk register Process | 3 | 1 | AI system owner · once per ai system |
| AI interaction and use disclosure notices Process | 3 | 0 | Product owner · at launch and on material change |
| AI governance policy and accountability structure Policy | 2 | 1 | Executive sponsor for AI · annual |
| Technical documentation, model cards and instructions for use Process | 2 | 1 | Product or model owner · at launch and on material change |
| AI incident management and regulatory reporting Process | 2 | 0 | Incident coordinator · continuous |
| AI impact and fundamental-rights impact assessment Process | 1 | 0 | AI system owner · once per ai system |
| Prohibited and unacceptable-use screening gate Process | 1 | 0 | AI governance lead · once per ai system |
| AI system inventory and classification Process | 0 | 3 | AI governance lead · continuous |
| Post-deployment monitoring and drift detection Technical measure | 0 | 2 | AI system owner · continuous |
| Automatic event logging and record retention Technical measure | 0 | 1 | Engineering lead · continuous |
| Training-data provenance and copyright register Process | 0 | 1 | Model development lead · at launch and on material change |
| Accuracy, robustness, fairness and security testing Technical measure | 0 | 1 | Quality or testing lead · at launch and on material change |
Every published duty whose record names this audience. It is the recorded set, not every rule in the world; a jurisdiction missing here may simply not be mapped yet (open gaps).
Informational only, not legal advice. Verify every claim against the linked official sources and consult qualified counsel before acting.
