Using data on more than 220,000 individuals on the Lyft rideshare platform, researchers report that drivers of color are significantly more likely to receive speeding tickets than white drivers, and to face steeper fines, even when traveling at identical speeds. Racial profiling by law enforcement is a pressing social issue in the United States. Previous research analyzing police and judicial records suggests that racial and ethnic minorities face disproportionately higher rates of searches, fines, force, detentions, and incarceration compared to white civilians. However, research on racial bias in policing has long been hindered by data limitations and challenging analyses. For example, to demonstrate racial bias in policing, researchers must compare officer treatment of minority and white civilians under identical circumstances, while also controlling for all other factors in a police-civilian encounter that might explain enforcement disparities. These so-called “all-else-equal” scenarios are scarce in policing research.

 

Leveraging high-frequency GPS location data from the rideshare platform Lyft, Pradhi Aggarwal and colleagues overcome some of these challenges and estimate the effect of racial profiling on citations and fines for speed violations. The analysis encompassed 222,838 Lyft drivers operating in Florida from 2017 to 2020. Lyft drivers use a smartphone application that transmits precise location and speed data to Lyft’s system at 10-second intervals, providing researchers with detailed, real-time driving information. Aggarwal et al. then matched this dataset with Florida’s government records for speeding violations, detailing traffic stops and driver’s license information for those involved. The authors found that minority drivers are significantly more likely to be cited for speeding and pay higher fines than white drivers, even after controlling for factors like driving speed, location, vehicle characteristics, and other relevant variables. The findings show that minority drivers are 24% to 33% more likely to be cited during a traffic stop and they pay 23% to 34% higher fines, compared to white drivers. Moreover, the analysis revealed no significant differences in accident or re-offense rates across White versus minority drivers, suggesting that policing bias – rather than driver behavior – drives these disparities. “Aggarwal et al. have provided a template for using recent technological advances to overcome some of the most challenging obstacles impeding policing research,” write Dean Knox and Jonathan Mummolo in a related Perspective.

 

For reporters interested in trends, a 2021 Science study led by Knox, and using a dataset on daily patrols of officers in the Chicago Police Department, reported that Black officers used force less often than white officers during a three-year period studied. https://science.sciencemag.org/cgi/doi/10.1126/science.abd8694

About The Study: In this pooled cross-sectional study, findings suggest that state legislatures that elected to increase their state minimum wage may have also improved state food security rates among households with children at risk for economic hardship. The findings provide policymakers with actionable evidence to consider in setting minimum wages that could reduce the burden of food insecurity among U.S. children and families.

A study finds that factors beyond a person’s control, like socioeconomic status and whether their mom smoked or was obese, can influence whether they are overweight or obese as teenagers or adults. Glenna Nightingale of the University of Edinburgh, UK and colleagues report these findings on March 26, 2025 in the open-access journal PLOS One.

Housing tends to be a key part of household wealth, but despite its importance, it has been difficult to measure the value of a property. In a new article, researchers studied the impact of a popular machine learning pricing algorithm on the U.S. housing market. The study found that, overall, the algorithm benefitted the market.