Dissecting Digital Design
# A city is not a computer
“libraries are not just places for the consumption of information and knowledge, but places for local communities to build their own collections and perform them,” Mattern tells me. That makes them a sort of antithesis to all the cameras, speed sensors, and Bluetooth location sensors that a “smart city” might use to suck data out of its inhabitants.
When innovating on software and computers, we have the luxury of tight feedback loops and isolated feature development. Meanwhile, adopting that approach with city-building creates a metric-driven tunnel vision that is prone to multiplying surveillance and exploitation.
Mattern asks how we can piece together interdisciplinary lenses to better understand cities, not through more data, but ==different data — specifically intelligence that blends binary logic, sensory experiences, and local knowledge.== Perhaps we should aspire not to a smart city, but a wise one.
“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 is ultimately much, much smarter than any supercomputer.”
We must also recognize the shortcomings in models that presume the objectivity of urban data and conveniently delegate critical, often ethical decisions to the machine. We, humans, make urban information by various means: through sensory experience, through long-term exposure to a place, and, yes, by systematically filtering data. It’s essential to make space in our cities for those diverse methods of knowledge production. And we have to grapple with the political and ethical implications of our methods and models, embedded in all acts of planning and design. ==City-making is always, simultaneously, an enactment of city-knowing — which cannot be reduced to computation==
- Libraries, communal learning, digital gardens, DAOs
- Fighting internet surveillance
- Miscellaneous Notes/Literature Notes/The Dark Forest Theory of the Internet - Literature Notes
- Recognize humanity; prioritize racial, digital and environmental justice (and other forms of information difficult to datafy)
- Related to SocSci13: evaluating cities through GDP vs HDI and other humane metrics