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Huffington Post: Facial Recognition Systems Turn Your Face Into Your Credit Card, PIN, Password

Huffington Post: Facial Recognition Systems Turn Your Face Into Your Credit Card, PIN, Password 1

Earlier this week, Finnish startup Uniqul released a YouTube video advertising its pay-by-face authentication system.

In Uniqul’s imagined future, faces will act like credit cards. At the checkout counter, you’ll give a “meaningful nod” to the scanner, which will use your biometric information to determine who you are and then deduct money from your account.

Adam Clark Estes of Gizmodo has already explained why Uniqul’s system is not yet fully feasible, for reasons financial and psychological. Nonetheless, Uniqul isn’t the first company to experiment with facial recognition as a method of identifying consumers.

Human faces are unique. Computers can, to a startling extent, distinguish them. Until recently, facial recognition was used commonly in a limited number of contexts: Think police work and social media. Now, several companies are looking to broaden its reach.

At a London ATM conference this summer, American security company Diebold demonstrated a prototype “Millennial ATM.” The new ATM uses facial recognition as a primary method of authenticating customers; you still have to scan a QR code before getting cash.

But should the Millennial model replace current ATMs, privacy advocates may not be pleased. To use Diebold’s ATM, you must let the controversial security company store a copy of your biometric measurements.

Another, less potentially invasive way to use facial recognition as authentication is to let your face be your password to access digital devices. This kind of open-by-face technology would avoid the “big corporation is storing my biometrics” problem: Your biometric info would have to be stored only on the device that you unlock with it.

New apps like KeyLemon and FastAccess Anywhere already let people use faces as smartphone and computer passwords. But beware: According to USA Today, FastAccess Anywhere’s system can be fooled by a photograph of a device’s user.

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