Redefining Choices. How Does Artificial Intelligence Support Decision-Making in Urban and Architectural Development?

In response to the increasing complexity of urban and architectural projects and the need for informed, viable, and objective problem-solving processes, this research examines the decision-making processes in urban and architectural realms. In particular, it explores how artificial intelligence (AI) can enhance specific stages of decision-support approaches. Through a combination of theoretical analysis with practical application, this thesis explores the use of Multi-Values Appraisal Methodology (MuVAM) to support decision-making in architecture with or without the support of artificial intelligence (AI). MuVAM is a new tool that combines problem structuring methods (PSMs) and multi-criteria decision analyses (MCDAs), offering a framework to address complex problems and evaluate multiple criteria. The research examines two aspects of the application of MuVAM: its stand-alone use, focusing on its ability to structure and analyze problems, and its integration with AI, exploring how this digital technology enhances its functionality. By addressing these complementary perspectives, the thesis highlights the features of MuVAM and the potential of AI in decision support systems. In particular, the thesis draws upon the observation and reporting of participants interacting in the workshops’ environment. The workshops were experimented with through three case studies, at different scales: (i) the transformation of the district “Pointe Nord” in Geneva; (ii) the adaptive reuse of the former Paracchi carpet factory in Turin; and (iii) the requalification of the San Salvario neighborhood in Turin. Each case study illustrates how structured decision-making, guided by the integrated methodology, can be applied in architecture to address site-specific challenges and optimize urban decision outcomes. Also, since the first one was performed without the use of AI combined with MuVAM, the applications were compared in this sense. Accordingly, by connecting theoretical research with practical experiments observation, the thesis highlights the challenges and opportunities of such integrations, incorporating decision-making processes and artificial intelligence into architecture.