BEng (Hons)(Civil Engineering), University of New South Wales, Australia MSc (Urban Planning), University of Melbourne, Australia
PhD Thesis Title:
PhD Research Summary:
As urban development evolves, the integration of artificial intelligence (AI) in smart city planning has emerged as a transformative force. The rise of generative AI, particularly domain-specific large language models (LLMs), has driven significant technological innovation. However, these advancements also present unique challenges due to the increasing complexity of urban phenomena, theories, and data. Issues such as hallucination and stereotype bias are not sufficiently addressed by general responsible AI principles, compromising the credibility of LLM applications in urban planning. Currently, there is no universally accepted framework to guide the responsible development and deployment of LLMs in this field. This gap makes it difficult to ensure the responsible use of LLMs in planning practices. This study seeks to develop a responsible framework that establishes principles and guidelines for creating trustworthy LLMs in urban planning. By providing a structured approach, the framework aims to facilitate successful collaborations between AI and urban planners, ensuring that technological advancements contribute responsibly to the creation of better urban futures. The ultimate goal of this PhD research is to support the responsible adoption of LLMs in urban planning, ensuring that their use enhances the quality and sustainability of urban development.