Many consider surge pricing to be one of the negative points of Uber. The ride-sharing service maintains that surge pricing allows it to ensure that passengers can always get a ride when they need one, even if it comes at an inflated cost. It’s not like the company hasn’t come under fire for using surge pricing and even though it won’t do away with it entirely, Uber says it’s going to use machine learning to reduce surge pricing.
Surge pricing is normally implemented when there’s too much demand in a given area. Passengers can find that their trips cost significantly more than they do on a day with normal demand, thus taking away the cost advantage that Uber promotes over conventional taxis.
Uber is looking to limit the use of surge pricing by using machine learning. The sophisticated computer algorithms that it creates will take in multiple data inputs to predict where the most demand is going to be, allowing Uber to redirect drivers there, and if there’s no supply and demand shortage it doesn’t really need to implement surge pricing.
The idea behind this initiative is to find user demand before it necessitates implementation of surge pricing, as Uber engineering lead Jeff Schneider explains that this is to “find those Tuesday nights when it’s not even raining and for some reason there’s demand — and to know that’s coming. That’s machine learning.”
Uber hasn’t confirmed when this system will be rolled out broadly to reduce instances of surge pricing.
Filed in . Read more about Machine Learning and Uber. Source: npr.org