AI-Driven Deconstruction of Urban Regulatory Frameworks: Unveiling Social Sustainability Gaps in Santiago’s Communal Zoning

Abstract

This article presents a novel methodology for auditing urban regulatory frameworks through the application of artificial intelligence (AI) using the case of Greater Santiago as an empirical laboratory. Based on the semantic analysis of 31 communal zoning ordinances (Planes Reguladores Comunales, PRCs), the study uncovers how legal structures actively reproduce socio-spatial inequalities under the guise of normative neutrality. The DeepSeek-R1 model, fine-tuned for Chilean legal-urban discourse, was used, enabling the detection of normative asymmetries, omissions, and structural fragmentation. Key findings indicate that affluent communes, such as Vitacura and Las Condes, display detailed and incentive-rich regulations, while peripheral municipalities lack provisions for social housing, participatory mechanisms, or climate resilience, thereby reinforcing exclusionary patterns. The analysis also introduces a scalable rubric-based evaluation system and GIS visualizations to synthetize regulatory disparities across the metropolitan area. Methodologically, the study shows how domain-adapted AI can extend regulatory scrutiny beyond manual limitations, while substantively contributing to debates on spatial justice, institutional fragmentation, and regulatory opacity in urban planning. The results call for binding mechanisms that align local zoning with metropolitan equity goals and highlight the potential of automated audits to inform reform agendas in the Global South.

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