The default recourse to data-fication, the presumption that all meaningful flows and activity can be sensed and measured, is taking us toward a future in which the people shaping our cities and their policies rarely have the opportunity to consider the nature of our stickiest urban problems and the kind of questions they raise. — Places Journal
What do corporate smart-city programs have in common with D.I.Y. science projects and civic hackathons? “Theirs is a city with an underlying logic,” writes Shannon Mattern, “made more efficient — or just, or sustainable, or livable — with a tweak to its algorithms or an expansion of its dataset.”
On Places, Mattern argues that the new wave of urban data science (and solutionism) is trending toward an obsession with data-for-data’s-sake and an idolization of landscape research methods.