AE
AI Ethics Review
🔵 Stable🕐 updated 2026-06-08
🔷 SkillSpec L3
pm-advanced
Conduct a structured ethical review of an AI or ML feature, model, or product. Use when preparing to deploy an AI system, assessing algorithmic risk, auditing a model for bias, or producing a responsible AI impact assessment. Produces a structured ethics review covering fairness, transparency, privacy, safety, accountability, and societal impact with a risk tier score, pre-deployment checklist, and prioritised mitigations.
📚 Based on NIST AI Risk Management Framework; Google PAIR
🗣 Say this to your agent
“Run an AI ethics review for [feature]”“Conduct an ethical impact assessment for our new ML model”“Review the AI risks for our hiring / credit / recommendation system”“Build a responsible AI checklist for our product”“What are the ethical risks of using AI for [use case]?”
What to give it
▸Feature or model name — and what it does
▸Who it affects — which users or people does the AI interact with, make decisions about, or collect data from?
▸What decisions or outputs it produces — recommendations, predictions, classifications, generation, automation?
▸Consequentiality — how significant are the AI's decisions? (low-stakes suggestions vs decisions that affect employment, credit, health, safety, etc.)
▸Data used — what training data, user data, or third-party data is used?
▸Human oversight — is there a human in the loop, and at what stage?
▸Deployment context — who will use this and how? (internal tool / consumer-facing / automated pipeline)
✅ The bar it holds itself to
Every skill in this library self-verifies — these are this skill's own quality checks, straight from its definition.
✓"Who is affected" includes people the AI makes decisions *about*, not just who uses the product
✓Fairness analysis names specific protected characteristics, not just "diverse groups"
✓Safety section covers both false positive and false negative failure modes
✓Accountability section names real people, not teams or roles
✓Mitigations are specific and time-bound — not "monitor and review"
⚠️ What it refuses to do
Do not limit the affected-population analysis to users of the product — AI that makes decisions about people (hiring, credit, content moderation) affects non-users who have no opt-out
Do not accept "we will monitor" as a mitigation without specifying what is monitored, at what threshold, and who acts
Do not assign fairness analysis to the model team alone — protected characteristic analysis requires input from legal, HR, or a subject-matter expert
Do not defer the DPIA to post-launch — for high-risk tier systems, a DPIA is a pre-requisite for lawful deployment under GDPR
Do not conflate statistical accuracy with fairness — a model can be 95% accurate overall while performing significantly worse for a protected group
Install
npx pm-claude-skills add --agent claude # or codex · cursor · gemini · hermes
# or one-line MCP (every skill, any client):
claude mcp add pm-skills -- npx -y pm-claude-skills-mcpRelated skills
🔌 Embed this skill
Drop this on your blog, docs, or site — it renders a "Run this skill" card:
<div data-pm-skill="ai-ethics-review"></div>
<script src="https://mohitagw15856.github.io/pm-claude-skills/embed.js" async></script>💬 Discussion
AI Ethics Review is one of 1078 open-source professional AI agent skills — all SkillSpec L3.
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