If you’ve ever taken an Uber, you’ve probably noticed the star rating system that lets you rate your driver after each trip.
It turns out those little stars are more than just feedback—they’re a powerful tool that can make drivers safer and more reliable.
New research on Uber drivers in Chicago shows that the app’s feedback system, combined with warnings and performance reports, can turn poor drivers into better ones.
In fact, the study found that Uber drivers, who face far fewer training and licensing requirements than taxi drivers, can perform just as well behind the wheel.
Uber takes a different approach from traditional taxi services. In Chicago, taxi drivers have to take a two-week course and pass a licensing exam.
Uber drivers, by contrast, simply pass a basic background and driving record check, and prove they have a license, insurance, and registration. Once they’re approved, they start driving.
Instead of relying on heavy upfront training, Uber monitors quality after drivers hit the road. After each trip, passengers can rate their ride from one to five stars.
If a driver’s average rating drops too low, Uber sends them a notification explaining they need to improve. The warning comes with links to resources to help them get better. Drivers who still don’t improve risk being removed from the platform.
Researchers from Stanford University, the University of Pennsylvania, and others studied nearly 6.9 million UberX rides in Chicago in early 2017.
They looked at passenger ratings alongside detailed driving data, like speed, braking, acceleration, phone use, and how close pickups and drop-offs were to the requested spots.
They found that riders gave higher ratings to trips where drivers maintained a steady, moderate speed, avoided sudden braking or acceleration, used their phones less, and got passengers to and from their exact locations efficiently. Shorter routes were also preferred.
The study revealed that when drivers received a warning about low ratings, they improved quickly. They drove more smoothly, sped less, handled their phones less, and picked up and dropped off riders more accurately.
Even more interesting, the improvements lasted—drivers kept up better habits even after they were told they were no longer at risk of being deactivated.
The researchers also tested whether giving drivers more detailed feedback could help. Some drivers received a dashboard showing trip-by-trip details of their driving behavior. These drivers, especially those in the bottom 10 percent for quality, improved more than those who only received basic weekly reports.
When the researchers compared UberX drivers to licensed taxi drivers hailed through the Uber Taxi app, they found the overall quality was about the same. Uber drivers tended to be smoother and more precise with pickups and drop-offs, while taxi drivers used their phones less and often took quicker routes.
The findings suggest that strict licensing and long training courses may not be the only way to ensure safe, high-quality service. Instead, real-time feedback, ratings, and data-driven reports—especially when supported by AI technology—can help workers improve on the job while keeping barriers to entry low.
As lead researcher Susan Athey put it, “We might be moving to a world where occupational licensing and other barriers, which may prevent workers from entering professions and keep prices artificially high, can be removed while maintaining service quality.
This may have fewer safety downsides than ever before.”
