UNESCO Recommendation on the Ethics of Artificial Intelligence — vendor disclosure form

1. Vendor identification

2. AI system identification

3. Provision-specific questions

1. AI in Employment. Will the offered system be used in employment-decision contexts within scope of UNESCO Recommendation on the Ethics of Artificial Intelligence (Policy Area 'Economy and Labour', para 116 — Member States to assess and address AI's impact on labour markets)? If yes, identify the specific employment decisions (hiring / monitoring / termination / promotion) and the assessment evidence you will provide.

   (Cite: Policy Area 'Economy and Labour', para 116 — Member States to assess and address AI's impact on labour markets)

2. AI in Healthcare. Will the offered system be used in clinical decision-support, diagnostic, or medical-device contexts within scope of UNESCO Recommendation on the Ethics of Artificial Intelligence (Policy Area 'Health and Social Well-being', para 121 — employ effective AI for health and the right to life)? Identify regulatory clearances (e.g., MDR / FDA / MHRA) held and any open conformity-assessment items.

   (Cite: Policy Area 'Health and Social Well-being', para 121 — employ effective AI for health and the right to life)

3. AI in Education. Will the offered system be used in automated grading, proctoring, or student-data analytics within scope of UNESCO Recommendation on the Ethics of Artificial Intelligence (Policy Area 'Education and Research', para 101 — provide adequate AI literacy education to the public)? Identify the educational stages covered and the human-oversight model.

   (Cite: Policy Area 'Education and Research', para 101 — provide adequate AI literacy education to the public)

4. Transparency Obligations. Provide the documentation required under the transparency obligations of UNESCO Recommendation on the Ethics of Artificial Intelligence (Principle 'Transparency and explainability', para 38 — people informed of AI-based decisions + right to request explanation) — including (as applicable) model card, system card, training-data summary, evaluation results, and known limitations.

   (Cite: Principle 'Transparency and explainability', para 38 — people informed of AI-based decisions + right to request explanation)

5. Individual Redress. Describe the end-user redress + complaint channel offered for the system, including documented appeal path and response-time commitment, consistent with UNESCO Recommendation on the Ethics of Artificial Intelligence (Policy Area 'Ethical governance and stewardship', para 55 — harms through AI investigated and redressed via enforcement + remedial actions).

   (Cite: Policy Area 'Ethical governance and stewardship', para 55 — harms through AI investigated and redressed via enforcement + remedial actions)

6. Training-Data Rights. Identify the legal basis for training-data sourcing for the offered system (including copyright, consent, and any text-and-data-mining exemptions relied upon) and confirm consistency with UNESCO Recommendation on the Ethics of Artificial Intelligence (Policy Area 'Data Policy', para 71 — data-governance strategies ensuring continual evaluation of training-data quality).

   (Cite: Policy Area 'Data Policy', para 71 — data-governance strategies ensuring continual evaluation of training-data quality)

7. Development-Rights Framings. Describe the offered system's compliance posture relative to the UNESCO Recommendation on the Ethics of Artificial Intelligence provisions identified at: Policy Area 'Development and International Cooperation', para 79 (+ Diversity Principle para 67) — AI-for-development bound to the values/principles.

   (Cite: Policy Area 'Development and International Cooperation', para 79 (+ Diversity Principle para 67) — AI-for-development bound to the values/principles)

8. International Coordination. Describe the offered system's compliance posture relative to the UNESCO Recommendation on the Ethics of Artificial Intelligence provisions identified at: Policy Area 'Development and International Cooperation', para 80 — platforms for international cooperation on AI.

   (Cite: Policy Area 'Development and International Cooperation', para 80 — platforms for international cooperation on AI)

9. Environmental Impact of AI Training. Provide energy + emissions disclosures for training + inference of the offered system as required or recommended under UNESCO Recommendation on the Ethics of Artificial Intelligence (Policy Area 'Environment and Ecosystems', para 84 — assess direct/indirect environmental impact incl. carbon footprint + energy consumption).

   (Cite: Policy Area 'Environment and Ecosystems', para 84 — assess direct/indirect environmental impact incl. carbon footprint + energy consumption)

4. Documentation enclosures expected

Tick each enclosure attached to the vendor response. Missing enclosures should be explained in the “Variances” field below.

• Transparency documentation (per-instrument schema)
• End-user redress + complaint-channel procedure
• Training-data summary / provenance log
• Safety / capability evaluation results
• Vendor company registration + insurance certificates
• Sub-processor / supply-chain list (including model upstream)

5. Vendor attestation

The undersigned, on behalf of the vendor, attests that the disclosures above are true and complete to the best of their knowledge at the date signed, and undertakes to notify the buyer in writing within 30 days of any material change to those disclosures.