The red-headed man wearing what looks like the ultimate Christmas sweater walks up to the camera. A yellow quadrant surrounds him. Facial recognition software immediately identifies the man as … a giraffe?
This case of mistaken identity is no accident — it’s literally by design. The sweater is part of the debut Manifesto collection by Italian startup Cap_able. As well as tops, it includes hoodies, pants, t-shirts and dresses. Each one sports a pattern, known as an “adversarial patch,” designed by artificial intelligence algorithms to confuse facial recognition software: either the cameras fail to identify the wearer, or they think they’re a giraffe, a zebra, a dog, or one of the other animals embedded into the pattern.
“When I’m in front of a camera, I don’t have a choice of whether I give it my data or not,” says co-founder and CEO, Rachele Didero. “So we’re creating garments that can give you the possibility of making this choice. We’re not trying to be subversive.”
Didero, 29, who’s studying for a PhD in “Textile and Machine Learning for Privacy” at Milan’s Politecnico — with a stint at MIT’s Media Lab — says the idea for Cap_able came to her when she was on a Masters exchange at the Fashion Institute of Technology in New York. While there, she read about how tenants in Brooklyn had fought back against their landlord’s plans to install a facial recognition entry system for their building.
“This was the first time I heard about facial recognition,” she says. “One of my friends was a computer science engineer, so together we said, ‘This is a problem and maybe we can merge fashion design and computer science to create something you can wear every day to protect your data.’”
Read More at https://edition.cnn.com/2023/01/16/tech/facial-recognition-fashion/index.html?