Uber wants to use machine learning to predict when a surge of people will be out looking for rides. The intention is to get more cabs on the road before surge pricing would normally kick in. That way, drivers will be ready and waiting for riders when the surge happens — and riders won't be stuck waiting around.
Here's how Jeff Schneider, the engineering leader of Uber's Advanced Technology Center, put it during a recent data technology conference: "This idea is if you can predict that demand, you get that information out there — and you get that supply there ready for the demand so the surge pricing never even has to happen," he said, according to NPR. Uber already does this to some extent, but Schneider says that Uber wants "to find those Tuesday nights when it's not even raining and for some reason there's demand."
"We have no plans to end dynamic pricing."
"Uber is always looking for ways to better predict supply and demand in a city. But this story is not accurate," Uber tells TechCrunch. "We have no plans to end dynamic pricing. While we understand that no one likes to pay more for the same trip, it’s the only way to ensure that passengers can always get a ride when they need one."
So how do these ideas square up? It's hard to say precisely right now, but it's easy to understand why surge pricing can't go away. Surge pricing is what Uber uses to get drivers on the road — if it did away with surge pricing, it wouldn't have a way of meeting that demand, even if it managed to see it coming ahead of time. It seems more likely that Uber could use this information to activate surge pricing early, so that it ensures plenty of drivers are ready when demand actually spikes.
Basically, don't be surprised if surge pricing is a thing even when Uber's entire fleet is replaced with self-driving cars. Predictive tech will just help Uber know where and when it's going to need vehicles.