AI Roundtable, Part 3: From Transit Data to Better Predictions

In the third installment of Stop Requested’s AI Roundtable series, ETA CEO John Maglio joins hosts Levi McCollum and Christian Londono, along with Derrick VanGennep of Voloridge Investment Management, to explore how machine learning can help transit agencies move from understanding what happened to predicting what might happen next. The conversation covers data quality, model validation, uncertainty, and what happens when conditions change or an organization acts on a prediction. The group also explores potential transit applications including ridership, maintenance, on-time performance, and bus bunching, and why agencies looking to use predictive models should start with the decisions they need to make and the data required to support them.