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Maybe it’s one topical – I think I used it myself – to explain how scientists and philosophers work with the brain to say that they are metaphorically following the most advanced technology of their time. According to Greek writers, the brain functioned similar to hydraulic water clocks. In the Middle Ages, European writers suggested that thought functioned through gear-like mechanisms. In the century the brain was like a telegraph; a few decades later, it was like a telephone network. Soon, unsurprisingly, people thought that the brain could function like a digital computer and maybe they could build computers that function like the brain, or talk about it. It’s not easy, metaphors aside, no one really is he knows how the brain works. It can be science exciting Like that.
Not having a good metaphor hasn’t stopped anyone learning brains, of course. But sometimes they confuse the map with the earth, confusing it with a good metaphor for viable theory. It is easy to make a complete observation of complex systems that interact too large or too small in scale. That’s true for the brain, the meat of thought, which creates the individual mind, the researchers think, about 86 billion cells woven into an electrochemical network of gelatin. And it’s true for a city, a dense network that brings together millions of these minds to form a community. People who write about cities …I did it myself–also in modern science they are tempted to organize metaphors. A city is a machine, a city is an animal, a city is an ecosystem. Or maybe a city is like a computer. As for urban planner and media writer Shannon Mattern, that’s dangerous.
Mattern’s new book comes out on August 10; is a collection of some of his most intelligent work (with reviews and updates) Place magazine call A city is not a computer: other cities are intelligent. In it, Mattern found a certain metaphor in the twentieth century. He struggles with the ways he has screwed up the design, planning, and way of life of the cities of the century. It happens at all scales that if individual people are examined, as if they were bits, they should be controlled by wide-screen data in order for the city to function for the good of the inhabitants. Mattern says that of all the ways information travels from an urban network, it would probably be better for public libraries to have nodes than panoptic-like centralized panels that so many cities try to build. The problem is that people have become targets for the metrics they choose to follow. They become a kind of metaphor and are usually wrong.
The first two essays are the most influential when they were first published — and still are. The “City Console” is a wild history of information panels and control rooms designed to be panoptics for urban data. These information centers collect information on how municipal systems work, whether crime is being policeed, educating children, and so on. Mission control, but for highways and sanitation. My favorite example from Mattern’s book is a project by Salvador Allende, then the leader of Chile, to build something called Cybersyn, with an “ops room” that would make Captain Kirk proud, with a full chair that would make Captain Kirk proud. size screens with flashing red lights. Of course, as cities did not have real-time data to fill these screens, they showed hand-made slides instead. It’s goofy, but there’s a direct line from Cybersyny to the way many U.S. cities now enforce the law and collect and display data from other cities. CompStat programs. They think so accountable to the government, but they often justify invalid arrests or highlight misleading numbers: instead of people who traveled during transportation, let’s say.
In the next attempt, in the headlines, Mattern warns against the intentions of large Silicon Valley companies to build “smart cities”. When the attempt first appeared, Amazon was still under pressure to build a city-sized residence in New York City, and Google was making an effort to do the same in Toronto. (Google Project, a sibling company called Sidewalk Labs, would appear wooden skyscrapers, pavements that used lights, reconfigured flying uses, self-driving cars, and underground trash cans.) Now, of course, most high-tech-enabled projects in smart cities have failed or failed. The Hudson Yards in New York did not order (or perhaps threaten) its developers to deploy anywhere near the level of sensor and surveillance technology. Cities still gather and share all kinds of data, but they are not exactly “smart.”
In an interview last month, I asked Matterni why it seems like tech companies haven’t gotten a smart city, at least so far. He believes it was because they lost the most important parts of town planning. “Many of the more computational and data-driven ways of thinking about cities provide false knowledge,” says Mattern. City officials believe they are getting the raw truth when it comes to determining what filters they actually choose. “When everything is computational, or when we can operationalize even the more poetic and evolutionary aspects of a city at a given point,” says Mattern, “that makes us aware that it is a metaphor.”
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