The AI that can STOP facial recognition:

Daily Mail

It could be the answer to the ever more invasive facial recognition systems used by Facebook, Google and others to try and identify you in every picture put online. Researchers at the University of Toronto have revealed AI software than can tweak your snaps so you can't be identified. They say their Instagram-like filter can tweak pictures so they look the same to human eyes, but disrupt machine learning systems used by web giants to identify users. Researchers from the University of Toronto have developed an algorithm specifically designed to disrupt facial recognition systems. The technology uses a deep learning technique called adversarial training, which puts two artificial intelligence algorithms against each other.


AI claims to be able to thwart facial recognition software, making you "invisible"

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A team of engineering researchers from the University of Toronto has created an algorithm to dynamically disrupt facial recognition systems. Led by professor Parham Aarabi and graduate student Avishek Bose, the team used a deep learning technique called "adversarial training", which pits two artificial intelligence algorithms against each other. Aarabi and Bose designed a set of two neural networks, the first one identifies faces and the other works on disrupting the facial recognition task of the first. The two constantly battle and learn from each other, setting up an ongoing AI arms race. "The disruptive AI can'attack' what the neural net for the face detection is looking for," Bose said in an interview.


Researchers develop AI to fool facial recognition tech

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A team of engineering researchers from the University of Toronto have created an algorithm to dynamically disrupt facial recognition systems. Led by professor Parham Aarabi and graduate student Avishek Bose, the team used a deep learning technique called "adversarial training", which pits two artificial intelligence algorithms against each other. Aarabi and Bose designed a set of two neural networks, the first one identifies faces and the other works on disrupting the facial recognition task of the first. The two constantly battle and learn from each other, setting up an ongoing AI arms race. "The disruptive AI can'attack' what the neural net for the face detection is looking for," Bose said in an interview with Eureka Alert.


Here are the 7 requirements for building ethical AI, according to the EU commission

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In October, Amazon had to discontinue an artificial intelligence–powered recruiting tool after it discovered the system was biased against female applicants. In 2016, a ProPublica investigation revealed a recidivism assessment tool that used machine learning was biased against black defendants. More recently, the US Department of Housing and Urban Development sued Facebook because its ad-serving algorithms enabled advertisers to discriminate based on characteristics like gender and race. And Google refrained from renewing its AI contract with the Department of Defense after employees raised ethical concerns. Those are just a few of the many ethical controversies surrounding artificial intelligence algorithms in the past few years.


AI researchers design 'privacy filter' for your photos

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IMAGE: Researchers in U of T Engineering have designed a'privacy filter' that disrupts facial recognition algorithms. The system relies on two AI-created algorithms: one performing continuous face detection, and another... view more Each time you upload a photo or video to a social media platform, its facial recognition systems learn a little more about you. These algorithms ingest data about who you are, your location and people you know -- and they're constantly improving. As concerns over privacy and data security on social networks grow, U of T Engineering researchers led by Professor Parham Aarabi and graduate student Avishek Bose have created an algorithm to dynamically disrupt facial recognition systems. "Personal privacy is a real issue as facial recognition becomes better and better," says Aarabi.