AI Ethics Review Checklist Template

Overview

Ethics review is meaningless without structure. Vague discussions about "being ethical" don't surface specific risks or drive concrete mitigations. Organizations need systematic assessment tools that ensure consistent, comprehensive evaluation across all AI systems.

This ethics review checklist provides that structure. It transforms ethics review from subjective conversation to rigorous assessment with documented findings, risk ratings, and clear approval decisions. Use it as the operational tool for ethics committee reviews, project gate evaluations, or periodic ethics assessments.

What's Inside

• Review Stage Identification: Pre-development, pre-deployment, post-deployment, or periodic review—with appropriate focus for each stage
• Fairness & Bias Assessment: Training data evaluation (source documentation, demographic representation, historical bias, update processes), model output testing (disparate impact, fairness metrics, segment performance, adversarial testing, drift monitoring)
• Protected Characteristics Evaluation: Specific assessment across race/ethnicity, gender, age, disability, religion, national origin, sexual orientation, and socioeconomic status
• Transparency & Explainability: AI disclosure to users, content identification, capability documentation, decision explanation, factor disclosure, and explanation request processes
• Accountability & Human Oversight: System ownership, human review requirements, override capabilities, appeal processes, rollback mechanisms, audit trails, and governance roles
• Privacy & Consent: Informed consent verification, user awareness, data minimization, opt-out capabilities, access/deletion rights, anonymization, and retention limits
• Safety & Security: Risk assessment, malicious use safeguards, adversarial attack testing, decision limits, unintended consequence monitoring, incident response, and edge case testing
• Societal & Environmental Impact: Broader impact consideration, job displacement, human dignity, surveillance potential, environmental costs, and underserved community benefits
• Risk Summary Matrix: Category-level risk ratings (Low/Medium/High), mitigation status, and key concerns
• Approval Decision Framework: Clear outcomes—approved, approved with conditions, requires additional review, or not approved
• Sign-Off Workflow: Ethics reviewer and project owner approval documentation

Who This Is For

• Ethics Officers conducting formal ethics reviews
• AI Governance Teams establishing ethics review processes
• Project Managers preparing for ethics gate reviews
• Product Leaders ensuring ethical AI development
• Compliance Officers integrating ethics with governance

Why This Resource

This checklist makes ethics review operational. Instead of abstract principles, reviewers have specific questions to answer. Instead of subjective impressions, they document evidence. Instead of unclear outcomes, they reach explicit decisions with documented rationale.

The checklist is comprehensive but efficient—it covers all key ethics dimensions without requiring excessive documentation for low-risk systems. Risk ratings help focus attention where it matters most.

FAQ

Q: How long does a typical ethics review take using this checklist?

A: For low-risk systems with good existing documentation, 2-4 hours. For high-risk systems or those with limited documentation, 1-2 days. The checklist is designed to scale—not every question requires deep investigation for every system.

Q: Should this be used for all AI systems?

A: The checklist can scale to any AI system, but depth of review should match risk. Low-risk systems may warrant a quick pass with focus on red flags. High-risk systems (decisions about people, sensitive data, vulnerable populations) warrant comprehensive review of every section.

Q: How do we handle items marked "Needs Attention"?

A: Items that can't be answered "Yes" should be documented in the risk summary with mitigation plans. The approval decision (approved with conditions, requires additional review, not approved) depends on severity and whether mitigations are adequate.