Digital inclusion and Urban AI: strategic roadmapping and policy challenges

In the early decades of the twenty-first century, the lexicon of urban studies was reconfigured by the pervasive invocation of the "Smart City" [32][33][34][35]64].Proponents of this vision-often anchored in technocentric imaginaries-heralded a future in which digital technologies, data analytics, and networked infrastructures would solve the intractable challenges of urban governance, service delivery, and citizen engagement [8, 36, 37, 42-45, 72, 87, 88, 113-117].Yet, as David Harvey (2008) reminds us, urbanism is never a neutral process: it is entangled with political economy [10,93], the exercise of power [2], and the contestation of space [39].The so-called "Smart City" era, while promising efficiency and innovation, often obscured the asymmetries it reproduced-deepening digital divides, privileging corporate control over urban data, and underplaying the nuanced realities of human and planetary wellbeing [17].Building on Richard R. Nelson's seminal metaphor in The Moon and the Ghetto (1977) and his later reflection (The Moon and the Ghetto revisited, 2011), the persistent question-why societies can land humans on the moon but fail to resolve entrenched urban inequalities-resonates strongly in the age of Urban AI.As Fountain [54] argues, this dilemma now extends to the algorithmic domain, where the promises of AI risk reproducing structural biases unless governance frameworks explicitly target systemic inequities [51].The CIDOB report on Urban AI underscores this tension [56], warning that technological capabilities alone cannot bridge the socio-political gaps embedded in urban systems.Instead, innovation must be mission-oriented, context-aware, and equity-driven-principles that also underpinned the 2025 UIK Summer School on Digital Inclusion & Generative AI [24][25][26]