SDAIA AI Ethics Principles: A Pre-Deployment Review Checklist

SDAIA's official Artificial Intelligence page linked a 50-page English AI Ethics Principles PDF with 2025 on its cover when we checked it. The older link previously cited by this article still serves a different document: September 2023, Version 1.0. This revision uses the 2025 document and its printed page numbers. A search-result date or title is not enough to establish an edition; inspect the document itself.

The 2025 document describes seven principles: fairness; privacy and security; humanity; social and environmental benefits; reliability and safety; transparency and explainability; and accountability and responsibility. They begin on pages 12, 15, 18, 20, 22, 24 and 26. The matrix above turns those headings into proposed working questions, with a direct page reference for each principle.

Page 9 states the framework's scope across AI stakeholders in Saudi Arabia and describes little or no risk, limited risk, high risk and unacceptable risk. It says high-risk systems must undergo pre- and post-conformity assessments and describes unacceptable-risk uses as not allowed. Those are the document's words; this guide does not assign your system a category or decide what assessment process applies to it.

Page 31 labels the registration mechanism Optional Registration and describes optional reports for registered entities. That does not establish that every privacy, sector or other legal obligation is optional. Conversely, a paragraph in this guide is not evidence that every business needs the same license, job title or assessment. Ask the responsible legal and governance owners to document the applicable instruments, authority, scope and unresolved interpretation for the specific system.

Start with a system description: intended use, excluded use, users, affected people, model/application version and connections to other systems. Add a data-flow map and a record of permitted processing, test inputs and expected answers, observed failures, incident handling and the proposed rollout boundary. Mark missing evidence as missing rather than filling the space with a benefit statement.

The framework discusses lifecycle activities on pages 10–11, reliability tests and oversight on pages 22–23, traceability and third-party documentation on pages 24–25, and roles on pages 28–31. Our proposed evidence packet groups those concerns for a review meeting; it is not a reproduction of SDAIA's full controls or an exhaustive compliance checklist. Give each evidence item an owner, a version or date, and a location an authorized reviewer can open.

Assume an internal assistant answers from an approved equipment-support knowledge base and cannot modify business records. This is a fictional scenario, not a Ting client deployment or a completed benchmark. For a proposed test, give it a question whose answer is absent from the approved material. Expected behavior: explain that it lacks a supported answer and offer the agreed escalation path. Do not invent a pass rate or classify the system as low risk from this description.

Suppose the observed result in this fictional walkthrough is an unsupported answer and a non-working escalation link. Record the exact test/version, the failed expected behavior, the responsible application owner and the proposed action: remove the unsupported-answer path, repair escalation and repeat the relevant tests. Keep the affected release scope pending. A privacy review, authorization to use the documents and other necessary checks remain separate open items; passing this one test would not resolve them.

The downloadable JSON is a blank working record. Replace the placeholders locally with the system scope, evidence references, findings, responsible roles, proposed mitigations and a decision rationale. Its default status is pending review. It does not calculate a compliance score, issue an approval or upload the completed record to Ting. A review owner must define who can make the real deployment decision under the organization's applicable process.

For every unresolved material issue, record the next action and who owns it. If the scope changes, identify exactly what remains excluded and what evidence supports the narrower decision. Do not describe an unresolved issue as closed because a checklist row has text in it. The framework's roles section includes entity leadership/CDO, compliance, responsible AI and assessor responsibilities; our record asks for accountable roles without asserting that its field names create new statutory hiring duties.

A pre-deployment record needs a handoff. The framework describes continuing monitoring, performance information, incident logs and assigned alerts in its deployment controls, including pages 23, 25 and 28. Our recommendation is to record the chosen metrics, failure thresholds, alert recipient, rollback owner and events that reopen the review, such as a changed data source, model version, user group or action permission.

Keep the source edition and review date with the record. Recheck applicable guidance and requirements when the system or regulatory context changes; do not merely advance a date on an unchanged checklist. If you need help mapping the workflow, assembling a test plan or identifying missing ownership, the related audit and validation services are next steps—not promises of SDAIA approval.