By Ray Bert
A City Is Not a Computer: Other Urban Intelligences, by Shannon Mattern. Princeton, New Jersey: Princeton University Press, 2021; 200 pages, $19.95.
Everything, it seems, is “smart” these days. Smart watches, smart fitness equipment, smart appliances, smart thermostats, even smart buildings. Our cellphones have been so smart for so long that we’ve mostly dropped the “smart” in lieu of it being essentially implied. (Never mind that it arguably makes just as much sense to drop the “phone” part of the name for being too limiting.)
But in the world of architecture and urban planning, an even broader application has been taking hold: “smart cities.” The goal of achieving smart cities is politically and economically sloganable and all but inevitable due to the explosion of connectivity, data collection, and analysis. And it is seen in many quarters as a mostly unalloyed good. But there is a growing movement to push back and point out the limitations of city planning models that are too beholden to the computational, the algorithmic.
“After more than a decade of writing about similar themes in article form, I’ve pretty much had it with ‘smartness,’” writes Shannon Mattern, Ph.D., author and anthropology professor at the New School for Social Research in New York City. “I’m annoyed by its elasticity, ubiquity, and deceptiveness — and its sullying association with real estate development, ‘technosolutionism,’ and neoliberalism — so I plan to use the term as infrequently as possible.” And with that, A City Is Not a Computer is off and running with a forceful, frequently pointed, and intellectually dense critique of the smart city “orthodoxy” and the ways in which overreliance on technology and computational models “shape, and in many cases profoundly limit, our understanding of and engagement with our cities.”
The book first examines the evolution of the modern “urban dashboard” of a variety of metrics, even delving (unsurprisingly) into the anthropological background of such “dashboard views” from automobiles to aviation to computing and more. The analysis notes that while dashboards reveal much, they obscure or ignore many other, more difficult to measure factors. Those factors are explored in the second chapter and range from a city’s collective local knowledge to its cultures and history and other things that — as much as cleanliness, efficiency, or modernity — help define what a city “feels like” and whether it truly works for all its residents.
Chapter 3 focuses on one specific avatar of what Mattern calls the “urban knowledge infrastructure” that is poorly captured and often outright ignored by smart city designers: public libraries. What if, this chapter posits, cities invested in libraries the way they invest in financial centers or prisons? How valuable could they become? What else could they be reimagined as? How much more could they contribute to the lives of cities?
The final full chapter focuses on discrete areas of necessary urban infrastructure maintenance — defined as not just the physical part most familiar to ASCE members but also the labor force and health care services and, of course, the digital underpinning, which must continue humming properly.
“A city built to recognize the wisdom ingrained in its trees and statuary, its interfaces and archives, its marginalized communities and more-than-human inhabitants,” Mattern writes, “is ultimately much, much smarter than any supercomputer.” That lofty statement elegantly wraps up the argument implicit in the book’s title, well supported by the evidence cited throughout: Cities are more than the sum of their data.