TechForge

June 12, 2018

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.

 Interested in hearing industry leaders discuss subjects like this and sharing their use-cases? Attend the co-located AI & Big Data Expo events with upcoming shows in Silicon Valley, London and Amsterdam to learn more. Co-located with the  IoT Tech Expo, Blockchain Expo and Cyber Security & Cloud Expo so you can explore the future of enterprise technology in one place.

About the Author

Senior Editor

Ryan Daws is a senior editor at TechForge Media with over a decade of experience in weaving narratives and dissecting complex topics. His articles and interviews with industry leaders have earned him recognition as a key tech influencer from numerous organisations. Under his leadership, publications have been praised by analyst firms for their excellence and performance. Connect with him on X, Mastodon, Bluesky, Threads, and/or LinkedIn.

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