AI Ethics Review

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.

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-mcp

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)

Related skills