Time to Upgrade Our Tools: Integrating Urban Data Science into Economic Development Research and Curriculum.

This article examines the emerging role of urban data science (UDS) in economic development research, education, and practice, highlighting its slower adoption by economic development planners compared to urban planning fields. It contrasts traditional ("old") UDS methods—such as regression models grounded in social science theory—with newer ("new") UDS approaches that leverage machine learning and large-scale, real-time, user-generated urban data for prediction and forecasting. The article identifies current successes in descriptive, explanatory, and forecasting studies using UDS, while noting challenges including limited theoretical integration, educational gaps, and ethical concerns related to privacy and data representation. To advance the field, it calls for interdisciplinary collaboration, enhanced professional training, curriculum innovation, and the development of ethical guidelines and data infrastructure to better equip researchers, educators, and practitioners in economic development.