The smart city is a perpetually unrealized utopia | MIT Technology Review
▻https://www.technologyreview.com/2022/06/24/1053969/smart-city-unrealized-utopia/?truid=a497ecb44646822921c70e7e051f7f1a
While urban theorists somewhat myopically trace the concept of the “smart city” back to the 1990s, when IBM arguably first coined the term, the CAB’s research represents one of the earliest large-scale efforts to model the urban environment through “big data.” Utilizing a combination of computerized data gathering and storage, statistical cluster analysis techniques, aerial-based color infrared photography (what we today call remote sensing), and direct “on the ground” (i.e., driving around the city) validation of the aerial images, the CAB’s analysis was decidedly different from previous attempts. The CAB partitioned the city into clusters representing social-geographic features that sound straight out of today’s social media playbook: “LA singles,” “the urban poor,” “1950s-styled suburbs.” What the cluster analysis truly revealed were correlations between socioeconomic forces that could be used as predictors for which neighborhoods were falling into poverty and “urban blight.”
Though innovative for the time, the CAB’s harnessing of punch cards and computer-based databases was not an isolated endeavor. It was part of a much larger set of postwar experiments focused on reimagining the urban through computational processes. The urban theorist Kevin Lynch’s 1960 Image of the City spurred years of research into cognitive science on how we map typological elements in urban space (paths, edges, nodes, districts, and landmarks). Cyberneticians such as Jay Forrester at MIT sought to apply complex systems dynamics by way of computer simulations to understand the feedback loops within urban development, involving everything from population and housing to the influence of industry on growth. With Forrester, Lynch, and others, the foundations for smart cities were being laid, just as sensing and computing were entering into the public consciousness.
The contemporary vision of the smart city is by now well known. It is, in the words of IBM, “one of instrumentation, interconnectedness, and intelligence.” “Instrumentation” refers to sensor technologies, while “interconnectedness” describes the integration of sensor data into computational platforms “that allow the communication of such information among various city services.” A smart city is only as good as the imagined intelligence that it either produces or extracts. The larger question, however, is what role human intelligence has in the network of “complex analytics, modeling, optimization, visualization services, and last but certainly not least, AI” that IBM announced. The company actually trademarked the term “smarter cities” in November 2011, underlining the reality that such cities would no longer fully belong to those who inhabited them.
When we assume that data is more important than the people who created it, we reduce the scope and potential of what diverse human bodies can bring to the “smart city” of the present and future. But the real “smart” city consists not only of commodity flows and information networks generating revenue streams for the likes of Cisco or Amazon. The smartness comes from the diverse human bodies of different genders, cultures, and classes whose rich, complex, and even fragile identities ultimately make the city what it is.
Chris Salter is an artist and professor of immersive arts at the Zurich University of the Arts. His newest book, Sensing Machines: How Sensors Shape Our Everyday Life, has just been published by MIT Press.