The fashion industry is leading the fight against facial recognition technology

As facial recognition technology becomes more ubiquitous, people are starting to fight back, with fashion designers leading the way.

  • A new clothing line aims to confuse surveillance cameras
  • The Hyperface project conceals wearers from facial recognition software
  • Phantom glasses block facial recognition tech
  • Incognitio is a minimalist mask that helps wearers avoid facial recognition
  • The role of fashion in the fight against mass surveillance

We are living in the age of mass surveillance, in which almost everything we do or say in public is monitored and recorded, often without our knowledge or consent. Driven in part by growing use by law enforcement agencies, facial recognition technology has soared in popularity in recent years, and this trend is expected to continue well into the future. According to a recent report published by MarketsandMarkets, the global facial recognition market is predicted to grow from $3.2 billion in 2019 to $7 billion by 2024. As facial recognition technology becomes more ubiquitous, it’s starting to feel like there are cameras watching us everywhere we go. They’re in our streets, bars, restaurants, shopping malls, airports, workplaces, and even our homes. And it seems that there’s nothing we can do about it. Or is there?

 A horizontal bar graph showing the value of the global facial recognition market in 2019, and its predicted value in 2024.
MarketsandMarkets estimates that the value of the global facial recognition market in 2019 is $3.2 billion, and it predicts that it will grow to $7 billion in 2024.

Facial recognition technology has come under increased scrutiny in recent years. While it undoubtedly provides several potential benefits, particularly when it comes to preventing and solving crime, there are far more privacy, safety, and legislation issues associated with the use of this technology. In addition to a lack of regulations surrounding its use, facial recognition technology has repeatedly demonstrated a disturbing lack of accuracy and bias against people of colour. As a result, a number of privacy and civil rights groups have called on governments to ban the technology outright. “Facial recognition really doesn’t have a place in society,” says Evan Greer, the deputy director of the digital rights group Fight for the Future. “It’s deeply invasive, and from our perspective, the potential harm to society and human liberties far outweigh the potential benefits.” Rather than wait for governments to heed these calls, artists, designers, and researchers from all over the world have decided to take matters into their own hands by designing clothing and accessories that can help people fool facial recognition algorithms.

A new clothing line aims to confuse surveillance cameras

Adversarial Fashion is a new clothing line designed by the computer security professional and amateur fashion designer Kate Rose. However, this clothing line is anything but ordinary. Unveiled for the first time at the DefCon cybersecurity conference in Las Vegas, items in the Adversarial Fashion collection feature a highly unusual design characterised by an assortment of license plate images. The main purpose of such an unorthodox design is not to make any kind of fashion statement, though, but to confuse automated license plate readers, which have become increasingly widespread in the United States in recent years.

Usually mounted on street poles, streetlights, highway overpasses, or mobile trailers, automated license plate readers use networked surveillance cameras and image recognition technology to track people’s whereabouts by linking their license plate numbers with specific GPS locations, dates, and times. However, this technology is far from perfect and tends to have problems with accuracy, often pulling in data from billboards and picket fences by mistake. This inspired Rose to try to design clothes that would be able to pull the same trick and convince the machine it was looking at a license plate, rather than a person.

The Adversarial Fashion line includes shirts, hoodies, jackets, skirts, and dresses, with prices ranging from $25 to $55. The website also includes DIY resources, such as APIs and image-editing tools, which allow anyone to design their own anti-surveillance clothing. Rose hopes her creation will be able to raise awareness about the invasiveness of facial recognition technology, and maybe even inspire people to fight back against it. “Part of this is just about teaching people how the technology works and improve their understanding about part of the surveillance state,” says Rose. “But it does really work. Even if it’s just one person wearing one of these, and it causes these cameras to ingest 10 to 50 plates which are total garbage, that’s doing something. This is still information that has to be stored and analyzed, all of which costs money. It makes the system slightly less useful. I would love to think of ways that this could be adopted by whole communities who say that they don’t want to be compliant with these systems.”

The Hyperface project conceals wearers from facial recognition software

A product of a collaboration between the Berlin-based artist and technologist Adam Harvey and the international interaction studio Hyphen-Labs, the Hyperface project takes a similar approach to Adversarial Fashion. However, instead of license plates, it involves covering clothing or textiles with patterns that appear to have facial features, such as eyes, mouths, and noses, in the hope that it can trick facial recognition software into registering them as a face. The idea is to take the computer’s attention away from the wearer’s actual face and focus it onto these false faces, flooding the system with thousands of false hits and making it unable to tell which faces are real.

Once printed onto a piece of clothing or textile, the patterns can be worn or used to blanket an area. “It can be used to modify the environment around you, whether it’s someone next to you, whether you’re wearing it, maybe around your head or in a new way,” explains Harvey. Based on ideal algorithmic representations of a human face, the patterns are designed to target specific algorithms, including OpenCV’s default frontal face profile, HoG/SVM-based edge detectors, and convolutional neural networks.

Phantom glasses block facial recognition tech

Created by designer Scott Urban, Phantom glasses are a new line of privacy eyewear designed to block some forms of facial recognition technology. More specifically, the glasses are designed to trick 3D dot matrix face-mapping systems, such as the one used in Apple’s Face ID, by reflecting infrared light back at its source. This allows them to prevent IR video cameras from capturing a clear image of your face or even registering it altogether. “The days of when privacy was equated to criminals is long gone,” says Urban. “Now it’s all going to be about corporations/governments using your face to know everything about you and gather all of your data into a neat little profile. I and many others would simply prefer to not be on their system.”

Besides facial recognition technology in smartphones, the increasingly popular infrared security cameras also rely on 3D dot matrix mapping. Usually installed at bars, restaurants, parking lots, and street corners, they use IR LED lights to illuminate a dark location and then capture the resulting image with a special camera. It’s considered to be one of the most accurate forms of facial recognition technology and could soon become the most common one as well. However, thanks to Phantom glasses, you won’t have to worry about that anymore. They will allow you to maintain your privacy everywhere you go, day or night. “I’m just providing an opt-out because the system is not an opt-in,” adds Urban. “It’s everywhere and unregulated.”

The Phantom glasses look like an ordinary pair of glasses, albeit with a slightly wider frame. They can also be outfitted with tinted lenses or with prescription lenses, as well as an optional pair of IR lenses that block IR eye-tracking, which has been highlighted as particularly invasive by several privacy groups. Phantom glasses work by illuminating the area around the eyes, which prevents IR surveillance cameras from obtaining biometrics data needed to establish a positive match. At the same time, the reflected IR beams distort your facial data to confuse 3D infrared mapping tech and protect your privacy. The glasses can be purchased for $142, with shipping expected to start in 2020.

Incognitio is a minimalist mask that helps wearers avoid facial recognition

Polish designer Ewa Nowak has developed a minimalist metal mask called Incognitio, which makes the wearer’s face unrecognisable to facial recognition algorithms. This face jewellery, as its creator describes the mask, is made of brass and features three prominent pieces: an elongated polygon that stretches across the wearer’s forehead and two circles positioned just below their eyes. The pieces are joined by a strand of wire shaped to fit the outline of the face and secured to the head behind the ears, just like a pair of glasses.

“The project touches on the subject of social surveillance and protection of one’s own image in public places. The object is designed to protect the image against face recognition algorithms used in modern cameras installed in public spaces,” explains Nowak. The mask works by obscuring key parts of the face, which prevents facial recognition algorithms from identifying the wearer. Nowak tested the mask on Facebook’s DeepFace algorithm by uploading several images of models wearing her creation, none of whom the algorithm was able to recognise. However, even though it attracted a lot of interest, the Incognitio mask is currently only a concept and it’s not known if and when it might be available for purchase.

The role of fashion in the fight against mass surveillance

Facial recognition technology has pervaded almost every aspect of our society, making it nearly impossible to escape its attention. While there’s no doubt that it can provide several important benefits, helping law enforcement agencies identify suspects, find missing children, or secure access to government buildings, it also comes with numerous privacy, safety, and legislation issues. Despite repeated calls from numerous privacy and civil rights groups to ban facial recognition technology, its market size continues to grow. In response, a number of artists and fashion designers have created clothes and accessories designed to help people avoid detection by facial recognition algorithms.

Most of the examples listed here are designed to exploit a known fault in mass surveillance systems. However, as technology continues to advance further, those faults are certain to be resolved eventually, which would make these products all but useless. Their creators are well aware of that, stating that they’re not meant to solve this problem, but rather educate people about how mass surveillance technology works and what they can do to fight it. “The systems that are used for artificially identifying any kind of image get better every day. The computer vision field is making constant advances. I know that my shirts may not work in a couple of years. I’ve seen old projects from other anti-surveillance artists which don’t work any more,” says Rose. “I feel it’s important to push back in any small way I can, even if I’m just one person.”

From clothes that use intricate patterns to confuse surveillance cameras to glasses and masks that block facial recognition technology, anti-surveillance fashion has become increasingly popular in recent years. While some of these designs have proven rather effective, it’s important that they’re not viewed as the ultimate solution to this issue, but as a way to prompt conversation about it. Despite the concerns, facial recognition technology is unlikely to go away. If employed properly, it can be a force for good, but governments need to find a way to address the privacy and safety issues associated with its use. Until that happens, anti-surveillance fashion may be your best bet to protect your

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This article is written by Richard van Hooijdonk

This article is written by Richard van Hooijdonk

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