Philip Ellis
News & Views
Pay using just your face!

Alibaba have trialled a game-changing new payment system in China; customers at a new KFC concept store called KPRO are able to pay for their meals using facial recognition technology. The ‘Smile to Pay’ programme, developed by Alipay, scans people’s faces and then requires them to input their smartphone number in order to complete a transaction. In addition to being highly convenient, this new method of payment is secure; the company is confident that the facial scanners are sophisticated enough to be able to tell the difference between a person’s face and just a photo of them.

“Facial recognition has existed for decades, but only now is it accurate enough to be used in secure financial transactions,” says Will Knight at MIT Technology Review. “The new versions use deep learning, an artificial-intelligence technique that is especially effective for image recognition because it makes a computer zero in on the facial features that will most reliably identify a person.”

The facial recognition market is huge, estimated to be worth $6.19 billion by 2020 according to In China, search giant Baidu is working on facial recognition systems capable of matching adults with their baby photos, and a travel solution which will enable people to collect train tickets simply by showing their face. They currently have a database of tens of thousands of faces, and report 99 per cent recognition accuracy.

Just as voice is carving out its own niche in the way that people search and complete tasks, so too will facial recognition disrupt the way we think of authentication and security; it’s already being widely reported that the next generation iPhone, due to launch this autumn, will replace its fingerprint scanning ‘home’ button with a facial scanner.

The benefits of facial recognition go far beyond commerce and security; facial scanners are being utilized in detecting early signs of disease, for instance. A recent article in The Economist even speculates that “systems that measure emotion may give autistic people a grasp of social signals they find elusive.” However, it also predicts that facial scanning will further enable or entrench unconscious biases when it comes to how employers choose to hire new talent, or security protocols at airports and sports venues.

We’ve reported before on how diversity in the development of any machine learning is crucial, and it bears repeating here. When white faces account for the majority of data-sets in facial recognition testing, it results in an unintentionally biased programme. If facial scanners are to become a ubiquitous part of how we live our lives, from using our phones to making everyday purchases, then they need to be for everyone.

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