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🧪 AI Bias Audit Lab — Adversarial Fairness Stress-Testing for ML Models

Run adversarial fairness audits on a simulated ML classifier: probe it with synthetic protected-group test cases, compute a live disparate-impact ratio, and see the four-fifths rule pass or fail in real time.

AI & Machine Learning2DModerate60 FPS📱 Mobile-adapted

⚙ Under the hood

This simulation explores the critical challenges of governing responsible AI development by allowing users to adjust parameters related to fairness, bias detection, and accountability within machine learning systems. By manipulating these controls, you'll gain insights into the complex trade-offs involved in building ethical and trustworthy AI.

AI EthicsFairnessAlgorithms

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install