City of Indexes
052-0630-18L | Elective course | CAAD Praxis
A City of Indexes is not exactly definable in geometric terms. In order to engeder it, one must consider n-dimensions, out of which none is correct nor false. In fact, all of them coexist simultaneously in a non-Euclidian condition, but rather a point and all its possible trajectories, reachable within a few digitations. Today, computers and computer networks provide this kind of mobile and instant operability, increasing our reach of action as citizens of a City of Indexes.
The aim of this course is to introduce the concept and implications of the abundance of information in our work as architects, in order to challenge the notions of models, computation, Big Data, complexity, Machine Learning and so on, which are relevant to the fields of architecture and urban design.
Each one of us carries a personal computer in our pockets. As we move through the city, we produce, collect, share, store, leave traces of our daily activities. In parallel to this, a myriad of online platforms such as Open Street Maps, Google Maps, Google Earth and Bing populate the web presenting assumptions of a top-down, objective representation of the world, which we would like to question. Yet, what if we could be able to project our own perception and experience of the city on top of this generic common ground? Could we know which our favourite neighbourhoods in a city would be, even before having ever been there and without having read any touristic guides? This is a guided tour towards Big Data and Machine Learning for architects. By digging into the bigness of these generic-mapping services, we will identify “spatial brands” of the city. Afterwards, by accessing these spaces physically and collecting data we will experience and qualify them from an individual perspective, creating our own personal datasets. Using Machine Learning algorithms, we will confront these different views, see how they can learn from one another, and discuss how these concepts can be brought into our work as architects; taking the concept of City of Indexes as study case. This is not a coding class; it is a space for a deeper discussion around all these buzzwords that surround us. Become computer literate, understand what data is about and be able to make questions to the Big Plenty without feeling intimidated.