Leveraging Generative AI Models in Urban Science.

Abstract

Since the late 2000s, cities have emerged as the primary human habitat across the globe, and this trend is anticipated to continue strengthening in the coming decades. As we increasingly inhabit human-designed urban spaces, it becomes crucial to understanding better how these environments influence human behavior and how individuals perceive the city. In this chapter, we begin by examining the interplay between urban form and social behavior, highlighting key indicators of urban morphology, and presenting state-of-the-art methodologies for data collection. Subsequently, we harness the computational capability of foundation models, the latest Artificial Intelligence (AI) generation, to simulate interactions between individuals and urban built environments in a diverse group of 21 cities across the globe. Through this exploration, we scrutinize the models' capacity to encapsulate the intricate complexities of how individuals behave and perceive cities. These examples demonstrate the potential of advanced AI systems to assist urban scientists in understanding cities, emphasizing the necessity for a meticulous evaluation of their capabilities and limitations for the optimal application of Generative AI in urban research and policymaking.