Sense and the City. Towards a New Digital Common

Carlo Ratti | Daniele Belleri | SENSEable City Lab

The world today is awash with data. In 2016 alone, people produced as much information as was created in all of human history. Every time we send a message, make a call, or complete a transaction, we leave digital traces behind. We are quickly approaching the creation of what Italian writer Italo Calvino omnisciently called the “memory of the world”: a complete digital copy of our physical universe.

Such a scenario raises fundamental questions related to both who has access to data, and what data can be used for. As increasing distrust towards political institutions is apparent all over the world, our society finds itself at a turning point: data can become either an instrument exploited for private, adversarial interests or a tool to constitute a new positive “commons.” In other terms, to borrow Richard Buckminster Fuller’s words, we are at a “utopia or oblivion” crossroads.

To foster a debate on the issues at stake, we should first take a step back from the heated debate on the relationship between democracy and the emerging “dataville.” What we want to suggest here is a reflection on the different types of data available today, their taxonomy, and their possible uses. The fundamental premise is that Big Data can also provide us—as planners, engineers, designers, and, above all, citizens—with new tools to understand and transform the spaces we live in. If we take the right steps today, the city of tomorrow could evolve into an open platform to foster civic engagement—a kind of new commons based on the shared knowledge of the city.

As a starting point towards that goal, what we would like to propose here is a classification of data—focusing on its acquisition method and its urban usage. After having described the proposed classification system, we will illustrate them using case studies taken from the present and past work of the MIT Senseable City Lab.

Treepedia sources Google Street View (GSV) panoramas, which are analyzed by artificial intelligence to measure “canopy obstruction”. This result is the formulation of a “Green View Index (GVI)” to compare human perception of the urban green from the street level in different cities. Image: Singapore
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