AI Ethics Review Skill

This skill produces a structured ethical review of an AI or machine learning feature, model, or product. Output covers fairness, transparency, privacy, safety, accountability, and societal impact — with risk scoring, prioritised mitigations, and a checklist suitable for governance review or responsible AI documentation.

⚠️ This skill provides a structured framework for identifying and documenting ethical risks. It is not a substitute for legal advice, regulated algorithmic impact assessments, or specialist ethics review required in specific jurisdictions (e.g. EU AI Act, UK AI regulation).

Required Inputs

Ask the user for these if not provided:

• 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)

Output Structure