Big data driver Urban environment.
I strongly believe in the benefits of knowing and knowledge. The discussions that we had at MIT’s Future of Cities seminar surprised me by the amount of skepticism and worries that new knowledge provided by “Big data” brings up in students of urban form. I did not expect so much mistrust and doubt of technology at MIT of all places. It is so human to be afraid of everything that pushes us forward and challenges our hardly gained (empirical) knowledge of Urbanism. Does this concern spring from Urbanist’s lack of knowledge and general inability to use “Big data” in practice?
Urbanism is such a complex science and nonetheless, there is a very little actual scientific method in its everyday implementation, theory, methods, and strategies. Due to my architectural and artistic background, I definitely have strong biases towards aesthetic order in Urbanism. My mission and passion is to improve existing and create new socially attractive urban spaces. Unfortunately, I am not a scientist and can only do that using the urban templates from the past that are based on dogmas and realities that no longer relevant. I believe that the goal of urbanist is to order and orchestrate the amalgam of chaos stemming from political, social, and economic forces in order to package in a form that multiplies the invested energies and provides comfort to its inhabitants. Yet, this is such an immense and unwieldy task that architects cannot possibly manage them scientifically as of today.
In order to accomplish that we need to retool the whole profession if it is a profession. We need to reinvent the thinking about the city, we need to reinvent ourselves to regain the lost relevance to the world. Having abstract architectural thinking is not enough; it will lead us to nowhere. Ability to analyze the existing urban chaos, predict its needs, and model its future behavior is where we need a computational power to step in. Data in architecture is in its infancy. Yes, we can use BIM to model the future of a building in order to manage its construction and predict its inputs and outputs. Yet, when it comes to the scale of a city we are powerless to model and order its behavior. We can analyze its outputs, but we cannot change it for better.
This is where we need the technology to wield this immense amount of data a city throws at us. We need a better model for rational and productive decision-making. Human intelligence has reached its peak and we need AI to untangle the complexities our collective brain has produced. We should stop marvel at the aesthetic ugliness of the urban mess and start unraveling its chaos, or alternatively, we should input this chaos into a machine and let it answer the ultimate question of life the universe and everything.
