Technology Can’t Save The City
Technology can’t save the city because the complexity of the city can’t be translated into formulas. That is the bold argument in a recent piece by Hanna Hurr for Real Life Mag. She makes the argument that it is impossible for “smart city” technologies to accurately capture the interactions betweens millions of subsets of people that inhabit a city. Cities are just too complex to model and as cities rapidly grow, so does the capacity for infinite complexity needed for such a project. She says:
“Not only do these tech companies consider the city a problem for them to solve rather than a public institution to participate in; but they also… predict apocalypse only to offer redemption. They pledge their intelligent, automated, big data-driven supervision of the “smart city” will solve everything from climate change to resource depletion.”
Is smart city technology only being deployed at a city-wide scale? Of course not, and it’s individual applications have inarguably changed cities for the better. Smart city technologies are ubiquitous and essential to solving current urban challenges. But the way this argument gains teeth is when look at recent large scale attempts to redesign cities. Underlying many recent proposals for technology-driven cities is the idea of starting first from a blank slate. In a recent proposal by YCombinator, a San Francisco based start-up accelerator, they state “we want to study building new, better cities” and this means starting from scratch, in citizen-less locations. One of Google’s Alphabet teams, Sidewalk Labs, wants to “reimagine cities from the internet up”. And the best way they think they can do this? By building their own test city, of course. For these grand visions of technology ‘saving’ the city to be realized, they must first be designed without the current challenges of public urban life.
The vision of the city as a “problem to be solved” ignores one of the key roles of the city- as a place for public life. How could we try to include for the experiential elements of the city in a model? If technology to improve cities is best designed without current problems getting in the way, how will these models fair when applied to the very real human experience in an existing city? How do we integrate the complexity of existing human behaviours into the way we are designing smart city technologies?
This is not to say that technological innovation can’t vastly improve the global quality of life, but grappling with the human experience when looking at technological urban innovation is key to the successful integration of smart city technologies. How do we find ways to balance the human experience with the modelled and quantified world?