Abstract
This paper is structured as an instrumental case study assessing the impacts of the incorporation of AI platforms within the iterative design process of a fifth-year undergraduate architectural studio. The topic of focus for the studio was the rewiring of energy and water infrastructures within the city of Madrid, Spain. Within the contemporary city, such urban infrastructures have tended to be moulded around a strictly top-down, public-to-private gradient. This unidirectional, innately hierarchical, and centralized approach to the provision of energy and water has been accompanied by a range of issues, including cascading systemic failures, low systemic resilience, and issues of inequitable access to resources. A more hybridized approach to urban infrastructural networks continues to gain traction within the discourse, one which takes advantage of the capacities of more decentralized systems and greater private stakeholder engagement, while not shying away from some of the benefits of more centralized systems. This studio was oriented towards achieving a deep dive into such hybridized infrastructural frameworks while leveraging artificial intelligence platforms for the purposes of accelerating and amplifying portions of the iterative design process, refining project narratives, and accelerating the student research process.
Published Version
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