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Uber rolls out new tech to identify those too drunk to ride

We’ve all been too drunk in the back of an Uber, but a patent filed by the company might put a clamp on our good times for good.

 

 

Being absolutely plastered in the back on Uber telling your life story to the driver whilst simultaneously not trying to repaint the decor with your dinner is an institution bordering on tradition.

However, it seems that the tidal wave of explosive too-much-funnery is not that much fun for those who drive us home, which is fair enough. To combat this measure Uber has decided to play the same role as the parent tasked to pick us up after the party, asking our tipsy selves how much have you had to drink?

Per CNN Money, the U.S. Patent and Trademark Office published an application Uber filed in December 2016. The application details a system that uses machine learning to predict an Uber user’s “state.”

Here’s the kicker, the English of the patent is quite elastic, as it never outright claims to focus on intoxicated clients. Instead, it looks to identify an overly “tired” passengers who “might have difficulty locating the provider’s vehicle.”

But take a look at the factors about a passenger’s ride request the system considers, and the subtext is obvious.

  • How accurately and quickly the passenger types in their information
  • The angle at which the passenger holds their device
  • The passenger’s walking speed

Now, once it has this info, the system compares your history with Uber, it then can adjust how Uber responds to your ride request. For example, it might only send you drivers who are experienced when dealing with your tipsy posterior (or what they consider your tipsy posterior), change the pick-up location to something well-lit, or choose to deny you a ride completely. According to the patent application, “When the likelihood [that a user is acting ‘uncharacteristically’] is comparatively very high, the user may not be matched with any provider.”

Don’t get me wrong, I’m all for increasing the peace and lessening harm caused to employees, but don’t judge me.

I’ve been far drunker than this.

 

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