Uber, Lyft pricing algorithms charge more in non-white areas
Occurred: June 2020
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A study by researchers at George Washington University found evidence that Uber and Lyft's pricing algorithms charged higher rates for rides to and from predominantly non-white and lower-income neighborhoods in Chicago.
The researchers analysed over 100 million ride-sharing trips in Chicago between November 2018 and December 2019, cross-referencing ride data with census information to examine racial demographics of areas traveled to and from.
They found that higher per-mile fares were charged when passengers were picked up from or dropped off in neighbourhoods with a higher percentage of non-white residents and lower-income areas, as well as areas with a higher percentage of highly educated residents.
The study found correlations between fare prices and demographics, even when controlling for factors like time of day, demand and speed.
Lyft disputed the study's findings, calling the analysis "deeply flawed" and arguing that race is not a factor in their pricing algorithms and that the study did not use actual demographic data of rideshare users.
The study added to ongoing concerns about algorithmic bias and discrimination in ride-sharing services, and highlighted the need for greater transparency and oversight in the use of algorithms for pricing and other decisions that can impact different demographic groups.
System 🤖
Lyft pricing algorithm
Uber pricing algorithm
Operator:
Developer: Lyft; Uber
Country: USA
Sector: Transport/logistics
Purpose: Calculate price
Technology: Pricing algorithm; Machine learning
Issue: Bias/discriminationox
Research, advocacy 🧮
Pandey A., Caliskan A. Disparate Impact of Artificial Intelligence Bias in Ridehailing Economy’s Price Discrimination Algorithms (pdf)
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Page info
Type: Incident
Published: August 2024