Tired of facial recognition cameras tracking your every move? Italian fashion may have the answer CNN Business

0 0
Read Time:5 Minute, 23 Second


Tel Aviv
CNN

The red-haired man wearing what looks like the best Christmas sweater approaches the camera. A yellow quadrant surrounds it. Facial recognition software immediately identifies the man as… a giraffe?

This case of mistaken identity is no accident, it is literally by design. The sweater is part of Italian startup Cap_able’s debut Manifesto collection. In addition to tops, it includes hoodies, pants, shirts and dresses. Each has 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 in the pattern.

“When I’m in front of a camera, I don’t have a choice to give them my data or not,” says co-founder and CEO Rachele Didero. “So we’re creating garments that can give you the ability to make that choice. We are not trying to be subversive.”

Didero, 29, who is studying for a PhD in “Textiles and Machine Learning for Privacy” at Politecnico di Milano, with a stint at MIT’s Media Lab, says the idea for Cap_able came to him when he was on an exchange masters at the Fashion Institute of Technology in New York. While there, he read about how tenants in Brooklyn had fought their landlord’s plans to install a facial recognition entry system in their building.

“That was the first time I heard about facial recognition,” he says. “One of my friends was a computer engineer, so together we said, ‘This is a problem and maybe we can combine fashion design and computing to create something you can wear every day to protect your data.’

Cap_able is an Italian startup whose first project is the Manifesto collection, with knitwear that protects facial recognition.

Coming up with the idea was the easy part. To make this a reality, they first had to find – and then design – the right “adversarial algorithms” to help them create images that fool facial recognition software. Or they would create the image (of our giraffe, for example) and then use the algorithm to adjust it. Or they set the colors, size, and shape they wanted the image or pattern to take and then had the algorithm create it.

“You need a mentality between engineering and fashion,” explains Didero.

Regardless of which route they took, they had to test the images against a well-known object detection system called YOLO, one of the most widely used algorithms in facial recognition software.

In a now-patented process, they would create a physical version of the pattern, using a computerized knitting machine, which looks like a cross between a loom and a giant barbecue. A few tweaks here and there to achieve the desired look, size and position of the images on the garment, and then they could create their range, all made in Italy from Egyptian cotton.

Didero says the current garments work 60% to 90% of the time when tested with YOLO. Cap_able’s adversarial algorithms will improve, but the software it tries to cheat could improve as well, perhaps even faster.

“It’s an arms race,” says Brent Mittelstadt, director of research and associate professor at the Oxford Internet Institute. He compares it to the battle between software that produces deep forgeries and software designed to detect them. Except the clothes can not download updates.

“You might buy it and then it’s only good for a year, two, five years, or as long as it takes to improve the system to a point where you’d ignore the approach that’s being used. trick them into first place,” he said.

And with prices starting at $300, he notes, these clothes may end up being just a niche product.

However, their impact may go beyond preserving the privacy of those who buy and wear them.

“One of the key benefits is that it helps create a stigma around surveillance, which is really important to encourage lawmakers to create meaningful rules, so that the public can more intuitively resist really corrosive and dangerous kinds of surveillance. ” said Woodrow Hartzog, a professor at Boston University School of Law.

Cap_able is not the first initiative to combine privacy protection and design. At the recent World Cup in Qatar, creative agency Virtue Worldwide came up with flag-themed face paint for fans looking to fool the emirate’s legion of facial recognition cameras.

Adam Harvey, a Berlin-based artist focused on data, privacy, surveillance and computer vision, has designed makeup, clothing and apps aimed at improving privacy. In 2016, he created Hyperface, a textile that incorporates “fake face computer vision camouflage patterns” and what could qualify as an artistic precursor to what Cap_able is trying to do commercially.

“It’s a struggle, and the most important aspect is that this struggle is not over,” says Shira Rivnai Bahir, a professor in the Data, Government and Democracy Program at Israel’s Reichman University. “When we go to street protests, even if it doesn’t protect us completely, it gives us more confidence, or a way to think that we’re not giving ourselves completely to the cameras.”

Rivnai Bahir, who is about to present her doctoral thesis exploring the role of anonymity and secrecy practices in digital activism, cites the use of umbrellas, masks and lasers by Hong Kong protesters as to some of the more analog ways people have fought the rise of machines. But these are easily detected and confiscated by the authorities. Doing the same based on someone else’s sweater pattern can be more complicated.

Cap_able launched a Kickstarter campaign late last year. He collected 5,000 euros. The company now plans to join the Polytechnic’s acceleration program, to perfect its business model, before presenting to investors at the end of the year.

When Didero gets dressed, he says people comment on his “cool” clothes, before admitting: “Maybe it’s because I live in Milan or New York, where it’s not the craziest!”

Fortunately, more modest ranges are approaching, with patterns that are less visible to the human eye, but can still confuse cameras. Flying under the radar can also help people wearing Cap_able clothing avoid sanctions from authorities in places like China, where facial recognition was a key part of efforts to identify Uyghurs in the northwestern region of Xinjiang, or Iran, which reportedly plans to use it. to identify women without hijab in the metro.

Big Brother’s eyes may be increasingly omnipresent, but maybe in the future he’ll see giraffes and zebras instead of you.

Happy
Happy
0 %
Sad
Sad
0 %
Excited
Excited
0 %
Sleepy
Sleepy
0 %
Angry
Angry
0 %
Surprise
Surprise
0 %

Average Rating

5 Star
0%
4 Star
0%
3 Star
0%
2 Star
0%
1 Star
0%

Leave a Reply

Your email address will not be published. Required fields are marked *