Facial recognition software has become increasingly common in recent years. Facebook uses it to tag your photos; the FBI has a massive facial recognition database spanning hundreds of millions of images; and in New York, there are even plans to add smart, facial recognition surveillance cameras to every bridge and tunnel. But while these systems seem inescapable, the technology that underpins them is far from infallible. In fact, it can be beat with a pair of psychedelic-looking glasses that cost just $0.22. Researchers from Carnegie Mellon University have shown that specially designed spectacle frames can fool even state-of-the-art facial recognition software.
Give us your feedback Thank you for your feedback. Last September, Stanford professor Michal Kosinski unleashed a torrent of controversy when he used artificial intelligence to attempt to predict peoples' sexual orientation from their faces. Now he has set himself the challenge of deciphering his subjects' political beliefs with similar software. The research is an illustration of what can be done with deep neural networks -- the type of machine learning behind much artificial intelligence, which spots patterns and makes predictions from large volumes of data such as text and images. Other image recognition technologies driven by neural networks are being developed for uses including reading signs for autonomous driving and automatically detecting weapons in airport security scanners.
The Calgary Police Service became the first force in Canada to start using facial recognition software to match suspects against a mug shot database this week, but it likely won't be the last. The use of facial recognition technology is growing not just in law enforcement and security fields but also in commerce. "One of the reasons face [recognition] is so popular is that face images exist of almost everybody," said Kevin Bowyer, an expert on biometrics and computer vision and chair of the department of computer science and engineering at the University of Notre Dame. Some cellphone apps use face recognition instead of passwords to give users access to devices. "You've got your driver's licence photos, you've got your identity badges wherever you work, so you've got this legacy of images that are easily accessible for everyone."