Smile to pay: AI just got smarter

While many of us are still catching onto the cardless cash phenomenon, this month e-commerce juggernaut, Alibaba, made paywave technology seem kitsch by allowing KFC customers to pay with nothing more than a smile.

The Alibaba promotional video shows a young female customer selecting payment via facial recognition and then authenticating the purchase by inputting her mobile phone number. The technology is being piloted in select KFC stores across China.

This technological leap is just another example of the lightening pace that machine learning is progressing with.
 
What exactly is machine learning?

Ever wondered how your iPhone knows where you live, or how long it will take to get from home to the office? Machine learning is so ubiquitous, that you have probably used it several times today without even knowing. This phenomenon is transforming the way we interact, and depend, on technology – hence it’s the hottest tech trend today.

Machine learning helps computers and devices to understand, learn, predict and even operate autonomously. It does this by looking at data and developing an algorithm to predict behavioural patterns. 

Facial recognition advances

The use of facial recognition technology is certainly not new – it has been around for over a decade. But only now is it accurate enough to be used in secure financial transactions. An obvious example; have you uploaded a photo only to have Facebook suggest whom you should tag in the image? This is because Facebook has an inbuilt facial recognition algorithm that predicts your friends faces based on facial features, like the distance between the eyes, nose and ears. 

Samsung have used the technology in their Galaxy S8 phones as a quick and easy way for users to lock and unlock the smartphone.

Other businesses are using the technology to analyze their customers’ faces in order to develop targeted marketing strategies based on gender, age and ethnicity. It’s also been used to help people trial products – everything from eyelash extensions to custom spectacles.

How secure is facial recognition technology?

Now, for those of you with a doppelgänger out there, I know what you’re probably thinking. How safe is it having my bank account linked to my face? 

The Samsung smartphone technology works by scanning patterns in the iris. Much like fingerprints, this part of your eye is unique and almost impossible to replicate, making it one of the safest parts of the face to identify you by. 

The Alibaba / KFC project differs slightly. A 3D camera located at the point-of-sale scans the customer’s face to verify their identity. Following this, a verification code is sent to the users phone for an added layer of security. It uses what is called a “live-ness detection algorithm” to detect things like shadows in order to prevent people from using photos and videos to trick the system.

Where to from here?

Alibaba’s latest experiment has taken this facial recognition algorithm to new heights. This technology has the potential to transform everything from policing to the way people interact every day with banks, stores, and their workplace – and could lead to significant efficiencies. Take, for example, the idea of navigating your office building without the need for a swipe card. 

Perhaps the next, most exciting cab off the rank is Chinese company’s Baidu’s efforts to incorporate facial recognition technology in its Apollo smart car due for release in 2020. The company’s significant investment in the technology not only hopes to deliver driver recognition, but also the ability to detect driver fatigue through facial scanning.

While many companies are embracing machine learning to improve products and services for their customers, many are still trying to understand how exactly to use it. The good news is, once a competitive advantage for companies armed with the brightest data scientists, there are plenty of open source tools available. Programs like AWS’ Amazon Machine Learning and Google’s Mainstream Machine Learning make it easy for developers of all skill levels to use machine learning technology. So as long as you have a computer and Internet connection, it’s possible to get started. The most important thing is actually getting started. 

Like all technology, it takes a little while to transcend into everyday lives – just like it did with internet banking, PayPal, BPay and Paypass.

Before long, paying with your smile will quite simply become the norm.

Andrea Walsh is CIO of media intelligence company Isentia.