How AI Is Learning Bias from Public Transit Data

AI Ethics with Fexingo: Bias, Safety, and Responsible Artificial Intelligence · Jul 16, 2026 · 7m

In this episode of AI Ethics with Fexingo, Lucas and Luna explore how AI systems are inadvertently learning bias from public transit data. Using a concrete example from the Los Angeles Metro, they show how predictive maintenance models trained on historical ridership data can systematically under-serve lower-income neighborhoods. They discuss the feedback loop where reduced service leads to less data, leading to even more reduced service, and what transit authorities can do to break it. The hosts also touch on the broader implications for urban planning and equity, and briefly note how…