By Richard Hack
Try as they may, the ridesharing leaders Lyft and Uber can’t seem to make their platforms bias free. And, yes, they have tried in multiple ways.
Currently, when riders book a trip, the drivers only receive information on the pickup location and ultimate destination. When accepted, the rider receives information about the driver including a face and car picture, as well as vehicle license plate number.
At the same time, however, the driver then receives the rider’s name, and, if they have uploaded a self-pic, they receive that as well. And here is where the trouble begins, according to Jorge Mejia, assistant professor of operations and decision technologies, at Indiana University’s Kelley School of Business, who ran a study published in the journal Management Science. Any customer picture that uses a LGBTQ rainbow filter is 3% more likely to be cancelled before pickup if the rider is caucasian and 8% more likely to be cancelled if Black or Latino.
“We found that underrepresented minorities are more than twice as likely to have a ride canceled than Caucasians; that’s about 3 percent versus 8 percent,” Mejia said. “There was no evidence of gender bias.”
Working with co-author Chris Parker, assistant professor in the information technology and analytics department at American University in Washington, Majia determined that ridesharing companies should use other data-driven solutions to take note of rider characteristics when a driver cancels and penalize the driver for biased behavior.
One possible way to punish drivers is to move them down the priority list when they exhibit biased cancellation behavior, so they have fewer ride requests. Alternatively, less-punitive measures may provide “badges” for drivers who exhibit especially low cancellation rates for minority riders.
But, ultimately, policymakers may need to intervene, Mejia said.