Key points are not available for this paper at this time.
This study investigates how artificial intelligence (AI) has transformed the epistemological foundations of urban planning over the past 30 years, a critical yet under-theorised area in planning scholarship. To address this gap, the study conducts a large-scale bibliometric analysis of 1353 peer-reviewed articles from Scopus, using VOSviewer and SciMAT for science mapping. ASReview, a machine learning–assisted tool, was employed to reduce selection bias during article screening, thereby enhancing methodological rigor. The findings reveal a shift from rational-comprehensive models to data-driven, algorithmic urbanism. More significantly, the study identifies a novel hybrid epistemological turn, wherein AI acts as a dynamic mediator between top-down infrastructures and bottom-up, using approaches such as citizen science. This challenges the view of AI as a purely technocratic tool and reframes it as a socio-technical system with the potential to enhance participatory and adaptive planning, while also fostering more authentic, faster, and reliable decision making. The originality of this study lies in critically linking AI’s technical evolution with its socio-political consequences. Its significance lies in showing how digital transformation is not merely altering planning tools but fundamentally reconfiguring planning itself in ways that are context-sensitive, inclusive, resilient, and ethically grounded.
Shabani et al. (Tue,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: