checklist

AI Use-Case Risk Assessment — Ethics & Safety Checklist

An interactive pre-launch checklist to evaluate bias, privacy, explainability, human oversight, operational controls, attribution, and rollback readiness for AI features. Saves responses and supports team review and mitigation planning.

Interactive Tool

AI Use-Case Risk Assessment — Ethics & Safety Checklist

This assessment helps teams surface ethical, privacy, explainability, and operational risks before piloting or expanding an AI feature. For each item, select 'Yes' when the requirement is met or 'No' when action is needed. Scoring guidance: count the number of 'No' answers. 0–1 = Low risk, 2–3 = Moderate risk, 4–5 = High risk, 6–7 = Critical risk. Use the Mitigation Plan field to capture next steps and owners.

Is the AI feature's intended benefit clearly described, measurable, and aligned with organizational goals and user needs? Does the team have concrete success metrics?
Are all data sources identified and authorized for this use? Have privacy, consent, and data minimization checks been completed, and is sensitive data appropriately protected or anonymized?
Are fairness objectives defined, test datasets representative, and plans in place for bias measurement and remediation? Have stakeholder groups likely to be affected been considered?
Can decisions or outputs be explained at the needed level for users and auditors? Are logging, model cards, versioning, and audit trails in place to reconstruct behavior?
Is there a defined human oversight model (review/override/escalation) for risky decisions? Are roles/responsibilities for human reviewers clear?
Are success/failure metrics defined and instrumented? Is there a monitoring plan, alerting, and a tested rollback or containment procedure if performance or safety thresholds are breached?
Will users and affected stakeholders be informed when AI is used? Are third-party models or data sources attributed as required by policy or contract?
Capture links to design docs, data inventories, model cards, privacy impact assessments, or other contextual information that reviewers should see.
Select the risk level that best matches the number of 'No' answers and your judgment. Use this to prioritize mitigation work.
Describe prioritized mitigation actions, owners, target dates, and acceptance criteria. If risk is High or Critical, list immediate containment steps and who will approve rollout changes.
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