AI-powered cameras dot streets worldwide, equipped to identify faces or license plates. But a public backlash is gaining momentum. Privacy concerns—lack of consent, data storage and use, and misuse risks—are motivating people to fight back. The De Flock project maps automated license plate readers (ALPRs) to raise awareness. Some resort to vandalizing ALPRs, while others craft "adversarial fashion" to evade surveillance cameras, like the Kickstarter project no Recognition, presented at DEF CON.

In 2025, cybersecurity expert Bill Swearingen began experimenting with a Python-based fuzzer targeting YOLO, a popular object detection framework. He developed a reinforcement learning algorithm generating colorful geometric patterns, tested against 11 object detection models. Successful patterns thwart systems, lowering confidence scores, sometimes to no detection. "Privacy is a human right," Swearingen says.

Cap_able and Urban Privacy sell physical garments. Cap_able’s patented method weaves motifs into jacquard knits, interfering with computer vision to classify wearers as animals or objects. "If we’re able to camouflage a person as something else, then we’re obtaining our goal," says founder Rachele Didero. Urban Privacy’s Faception Reloaded baffles Open CV-based facial recognition with abstracted face prints, slowing detectors. "The idea is to create false data," says cofounder Daniel Preuß.

Anti-surveillance fashion traces to 2010s art pieces by Adam Harvey and Kate Bertash’s 2019 Adversarial Fashion line. "Clothing is something you can actually buy and put on, unlike policy," says Niloofar Mireshghallah of Carnegie Mellon University. Real-world conditions might reduce effectiveness.