When 99% Accurate Still Means Thousands of Wrong Arrests

Biometric Accuracy vs. Investigative Reality For developers working in computer vision (CV) and biometrics, the "99% accuracy" headline is a dangerous vanity metric. In a controlled lab environment using high-quality datasets like LFW (Labeled Faces in the Wild), hitting 99% is the baseline. But when you deploy that model into a production environment - scanning against a database of a million records - that 1% error rate translates to 10,000 potential false positives.