Turn off facial analysis and image-based searches on the social web

Researchers at the University of Toronto have developed an algorithm to dynamically interrupt facial recognition systems. In the future, users of Instagram, Facebook and Co will be able to protect their photos from facial analysis in the form of a filter.

The new approach uses a learning method called “adversarial training,” in which two artificial intelligence algorithms compete against each other.

Filter changes pixels

“Privacy has become a real issue as facial recognition continues to improve,”

explains researcher Parham Aarabi.

“This is one way that beneficial anti-facial recognition systems can combat this capability.”

Aarabi and colleague Avishek Bose therefore designed two neural networks: one that can identify faces and a second that wants to disrupt the face recognition task of the first. The two constantly fight and learn from each other, creating an ongoing AI arms race.

The result of the data obtained is a type of filter that can be applied to photos in order to protect the privacy of the user depicted. The algorithm manipulates very specific pixels in the image, causing such small changes that they are almost imperceptible to the human eye.

“We create very subtle disturbances in the photo, but they are significant enough for the detector to deceive the entire system,”

so evil.

Technology for everyone

In addition to disabling facial recognition, the filter also disrupts image-based search, feature recognition, emotion and ethnicity assessment, and any other facial attributes that can be automatically extracted.

In the next step, the researchers want to make the filter accessible to users. This should be done either through a smartphone app or through a website. A private application would be particularly worthwhile for social networks such as Facebook or Instagram.

Since the tiny deviations are hardly noticeable, photos are not disturbed in their appearance.


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