Differential Privacy in Practice: What the Math Guarantees (and What It Doesn't) for AI Training Data
Differential privacy is the strongest mathematical privacy guarantee for ML training data — but the gap between formal ε-DP and deployed reality means many 'private' AI systems aren't nearly as private as advertised. This post bridges the math and the practice.