How Can Participatory AI Implement Problem Structuring Methods for Urban Sustainability Enhancement?

Within the dynamic realm of urban development, SDGs underscore the pivotal role of citizens’ engagement in nurturing inclusive and collaborative urban decision-making processes. This participatory ethos proves instrumental in comprehending the multifaceted impacts of choices, fostering co-design, and empowering communities. Participatory Artificial Intelligence (PAI) and Problem Structuring Methods (PSMs) emerge as a strategic approach to operationalize participatory practices within this context. This method article delves into the interconnected dynamics of PAI and PSMs, highlighting their potential to enhance collaborative problem-solving and propel urban sustainability. The research introduces a methodological framework that seamlessly integrates PSMs and PAI phases through the adoption of the Activity Theory and the Agile Methodology. This approach prioritizes a human-centric perspective, fosters collaboration and facilitates the achievement of common goals in a structured manner. By leveraging the capabilities of AI in data analytics, community engagement, and scenario planning within the context of PSMs, it is possible to navigate the intricate landscape of sustainability challenges with a holistic and well-informed approach. The present research intends to demonstrate how PAI and PSMs together form a synergistic approach able to define inclusive and sustainable urban strategies based on evolving urban contexts.