Adversarial fashion designers deploy AI-scrambling patterns to dodge facial recognition

Security researcher Bill Swearingen showcased a reinforcement-learning system at DEF CON that generates geometric patterns capable of fooling object-detection AI, including systems built on the popular YOLO framework. He tested the patterns against 11 face- and person-detection models, successfully lowering confidence scores or evading detection entirely, while companies like Cap_able and Urban Privacy already sell clothing woven with similar disruptive designs.