A recent study, which took a hard look at algorithmic bias, determined that racial discrimination could play a large part in the pricing on rideshare apps such as Lyft and Uber.
Akshat Pandey and Aylin Caliskan of George Washington University examined a data set of more than 100 million trips taken in Chicago between November 2018 and December 2019. 68 million of these trips were individual riders. The authors of the study explained that while “demand and speed” have the highest correlation with ride fares, riders “may be facing social bias if picked up in a neighborhood with a low percentage of houses priced less than the median house price of Chicago, or dropped off in a neighborhood with a low percentage of white people.”
“Basically, if you’re going to a neighborhood where there’s a large African-American population, you’re going to pay a higher fare price for your ride,” Caliskan told New Scientist last week.
Uber and Lyft have both broken their silence following the study, issuing statements in response to the study’s findings.
While an Uber spokesperson said that the company welcomes studies of this type to help obtain a deeper understanding of the effects of dynamic pricing, the rep also added that other “relevant factors” were not considered in the study, including time of day and neighborhood patterns and more.
A Lyft rep also pointed out that other factors contribute to pricing discrepancies. However, they “recognize” that systemic biases are “deeply rooted in society” and said that the company also commends studies of this kind that focus on the issue of “unintentional” technology discrimination.