Opportunities and Potential Bias in New Transportation Data

Technology companies that provide mobility services, such as ride-sharing or navigation, are awash in widespread, real-time transportation data. Uber, Lyft, Waze, Apple, TomTom, and others have gathered massive amounts of data about the behavior of people and vehicles across the country. They know how long it takes people to drive from home to work in the morning, which roads are most congested, where and when accidents occur, and more…

However, relying on these new data sets may result in unforeseen costs. This issue brief first considers congestion’s effects on the environment and the potential role of new data sources in solving congestion issues in the United States. It then considers the limitations of these data: how their vehicle-based focus could lead to a reliance on driving as the primary mode of transportation and how data sets are very likely imbued with demographic biases that may exacerbate challenges facing vulnerable populations.