Towards more inclusive AI systems in cities

Abstract

Artificial intelligence (AI) is increasingly embedded in urban infrastructures and governance, shaping how people, spaces, and futures are classified, prioritised, and managed. Yet, most AI systems are developed within a narrow set of linguistic and geopolitical contexts and exported globally, embedding particular epistemic assumptions into diverse urban environments. Even where formal inclusion metrics are met, such asymmetries can render certain populations and realities less legible within algorithmic systems. Prevailing approaches in digital inclusion – centred on fairness metrics, representation, or access – presume technologies as politically inert and bounded. Yet, the adaptive and probabilistic behaviour of contemporary AI disrupts this premise, challenging the idea that inclusion can be achieved through distributive fixes alone. We argue that inclusion in AI urbanism must be reframed not as a technical property or distributive outcome, but a relational, political condition. Under these conditions, inclusion concerns the capacity of urban actors to shape, contest, and revise AI systems over time. We develop a framework structured around three dimensions: upstream co-production, situated everyday practices, and the adaptive governance capacities through which AI systems remain open to intervention by downstream actors. Only by attending to these relational politics can urban inclusion operate as a meaningful basis for urban justice.