The tech is improving all the time, however. But it won’t sabotage existing systems that have been trained on your unprotected images already. Related Storyįawkes may keep a new facial recognition system from recognizing you-the next Clearview, say. The doctored training images had stopped the tools from forming an accurate representation of those people’s faces.
In a small experiment with a data set of 50 images, Fawkes was 100% effective against all of them, preventing models trained on tweaked images of people from later recognizing images of those people in fresh images. Wenger and her colleagues tested their tool against several widely used commercial facial recognition systems, including Amazon’s AWS Rekognition, Microsoft Azure, and Face++, developed by the Chinese company Megvii Technology. Unlike previous ways of doing this, such as wearing AI-spoofing face paint, it leaves the images apparently unchanged to humans. Give Fawkes a bunch of selfies and it will add pixel-level perturbations to the images that stop state-of-the-art facial recognition systems from identifying who is in the photos.
This technique is very close to a kind of adversarial attack, where small alterations to input data can force deep-learning models to make big mistakes. They make tiny changes to an image that are hard to spot with a human eye but throw off an AI, causing it to misidentify who or what it sees in a photo.
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“Selfies, in a sense, are the blending of our online and offline selves.Most of the tools, including Fawkes, take the same basic approach.
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With selfies, we decide how to present ourselves to the audience, and the audience decides how it perceives you,” said Julia Deeb-Swihart from Georgia Institute of Technology. “People project an identity that promotes their wealth, health and physical attractiveness. Selfies are an identity performance - meaning that users carefully craft the way they appear online and that selfies are an extension of that. Appearance was most popular among all age groups, researchers said. The older crowd (35+) shared them far less frequently (13 per cent). The under-18 age group posted about 30 per cent of selfies. Researchers noted that overall, an overwhelming 57 per cent of selfies on Instagram were posted by the 18-35-year-old crowd. They also found that most selfies are solo pictures, rather than taken with a group.
Researchers noted that the prevalence of ethnicity selfies (selfies about a person’s ethnicity, nationality or country of origin) is an indication that people are proud of their backgrounds. Selfies about a person’s ethnicity, nationality or country of origin is an indication that people are proud of their backgrounds. Then came ethnicity pics (13 per cent), travel (seven per cent), and health and fitness (five per cent).
After appearances, social selfies with friends, loved ones and pets were the most common (14 per cent). Pictures about looks were two times more popular than the other 14 categories combined. Researchers found nearly 52 per cent of all selfies fell into the appearance category: pictures of people showing off their make-up, clothes, lips, etc. They gathered the data by searching for hashtag ‘#selfie,’ on the popular picture sharing website and then used computer vision to confirm that the pictures actually included faces. Researchers from Georgia Institute of Technology in the US combed through selfie posts on website Instagram to determine what kinds of identity statements people make by taking selfies. More than half of the selfies clicked are about appearance of people, highlighting their make-up, clothes and lips, according to a study that analysed 2.5 million pictures on popular photo-sharing website Instagram.
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