CRAFTING SUSTAINABLE KNOWLEDGE IN THE GEN-AI AGE: EMERGING EPISTEMOLOGIES FOR THE BUILT ENVIRONMENT

Abstract

The rapid integration of Generative Artificial Intelligence (Gen-AI) into the built environment is transforming how knowledge is produced, interpreted, and applied in pursuit of sustainability. This study examines the emerging epistemological shifts associated with AI-mediated design and planning processes, with particular attention to how diverse knowledge systems interact in shaping sustainable built environment outcomes. This study aims to examine how Gen-AI mediates between human expertise, local and indigenous knowledge, and environmental data; identify epistemic opportunities and risks associated with AI-driven knowledge production; and propose a conceptual framework for sustainable knowledge creation in the Gen-AI era. A qualitative conceptual methodology was adopted, and a structured literature synthesis was conducted. The analysis focused on identifying patterns in knowledge inputs, AI mediation processes, and sustainability outcomes. The analysis identifies three key epistemic dynamics: epistemic augmentation, where AI enhances human analytical and design capacity; epistemic displacement, where algorithmic outputs risk overshadowing tacit or contextual knowledge; and epistemic justice, emphasising the need for inclusive integration of local and indigenous knowledge in AI-mediated systems. This study concludes that sustainable built environment practice in the Gen-AI era requires hybrid knowledge systems in which AI complements rather than replaces human and community-based expertise. The proposed conceptual framework highlights the interaction between diverse knowledge inputs, AI-mediated transformation, and sustainability-oriented design outcomes. It is recommended that future AI applications in the built environment prioritise transparent algorithms, participatory knowledge integration, and ethical governance to ensure context-sensitive and socially inclusive sustainability solutions.