Machine Learning

Uber wants to develop an intoxication-detecting algorithm

uber ai algorithm drunk assault
©iStock/Mlenny

Uber has filed a patent for a machine learning algorithm which can predict whether a rider is sober or not to improve the safety of its service.

The sobriety of a passenger is a big factor in the safety of both driver and rider. Drivers have been assaulted by inebriated passengers, and most of the sexual assaults conducted against Uber riders by drivers have been while they were intoxicated.

According to a CNN investigation, at least 103 Uber drivers have been accused of sexually assaulting or abusing passengers in just the past four years.

Cutting off the service for anyone who’s the slightest bit intoxicated doesn’t make business sense and is likely to cause more problems on a societal level than it solves.

Many use Uber to get home after a few drinks without any problem, and I’m sure most would agree that it’s much better for everyone than if they were to reach for their own car keys.

To determine the user’s level of sobriety, the patent describes Uber’s AI learning how each user typically uses their app. Unusual factors such as inaccurate pressing of buttons, typos, walking speed, and more will be taken into account.

Someone who is determined too intoxicated may be denied a ride, or paired up with a driver with skills or training for dealing with inebriated passengers. For their trouble, these drivers could be able to charge elevated rates.

If nothing else, it may save a few Uber cars from smelling of vomit.

What are your thoughts on Uber’s algorithm for detecting intoxication? Let us know in the comments.

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