From Smart Urbanism to the Data-Driven City: A Critical Appraisal

Abstract

From the smart urbanism of the 2010s to platform and artificial intelligence (AI) urbanism(s) of the present-future, the “data-driven city” has been imagined as a functional and controlled whole, driven and regulated by autonomous (humans off-the-loop) systems that have been fed through a powerful data infrastructure. AI urbanism, in particular, manifests the current climax of the long-standing desire to control digital technology in the city yet to come. An excessive focus on technology, however, risks de-contextualizing it from the wider economic and political landscapes.

While digital platforms have been structuring the fabric of daily urban life, colonizing almost any field of interest through their ecosystems and mobile apps, AI technologies are starting to make their way into cities with: autonomous vehicles, city brains, digital twins, and robotics. Advocates suggest these novel technologies have changed the geographies of their deployment—expanding beyond urban areas to regional and global contexts not confined to cities any more, rather on regional or global scales. Also, in their partnerships with city management—, cities no longer have an exclusive and central stage; instead, they participate in consortia with limited or secondary roles. Both these configurations have been framed as the “post-smart city.”

But is there a paradigm shift between these versions of urbanism? Has the “smart city” framework—the neoliberal project of linking private investment from technology firms into the management and governance of city living—substantially changed? And finally, what role is expected for cities to take in this uncertain and evolving scenario?

The “data-driven city” ought to be understood in tandem with the development of data capitalism and the enormous expansion of its data infrastructure, markets, and services. Thus, I invite to re-position this debate as an intensification of neoliberal (“smart” or “data-driven”) urbanism and its ideological assumptions: technological solutionism and smart mentality, and data extractivism, surveillance and control.