⚖️ Check Outputs for Bias and Fairness

We use AI in decisions that affect people and we have never checked whether it treats them consistently. Build me a fairness review app. For each use case that affects people, let me define in advance the tests to run and the groups to compare, recorded before any results exist so the measures cannot be chosen afterwards to suit the outcome. Record each test run with the date, the sample, the outcome rates by group, and the difference between them. Record findings with a severity, the action taken, and where a difference was reviewed and accepted, the reason and who accepted it. Keep the full history so a trend over time is visible. Add an AI agent that reviews the results, highlights the differences large enough to warrant investigation rather than flagging every variation, and drafts a plain summary of what was tested and what was found for a non technical reader. Make clear the app records the review and does not perform the statistical assessment, which needs a qualified person. Automate two things: a scheduled review reminder per use case at the frequency its risk level requires, and an alert when a result crosses a threshold I set. Three logins: a case owner, a reviewer, and a read only auditor.