SEAS researchers found the algorithm behind Uber’s and Lyft’s dynamic pricing upped the charges for riders traveling to and from disadvantaged areas.
Thinking of calling a rideshare service? Uber and Lyft passengers going to and from low-income and non-white neighborhoods may pay higher prices, researchers at the George Washington University recently found.
Aylin Caliskan, an assistant professor of computer science in the School of Engineering and Applied Science, and doctoral student Akshat Pandey analyzed a public data set from the city of Chicago containing the times, pickup locations and destinations of more than 100 million rideshare trips. By comparing that information with census data about Chicago’s demographic makeup, the team discovered that riders were charged more per mile when they were traveling to or from neighborhoods with high percentages of nonwhite or low-income residents.
“It means people in these neighborhoods that are already disadvantaged are being further disadvantaged by having to pay more for their rides,” Dr. Caliskan said.
The culprit isn’t conscious prejudice on the part of individual drivers or the companies themselves, Dr. Caliskan said. Rather, it’s societal bias built into the decision-making algorithm that drives rideshare pricing.