Category: Uncategorized

Tabula Rasa: New Songdo.

At the centre of Songdo’s marketing materials and technical discourse lies a fantasized transformation in the management of life – human and machine in terms of increased access to information and decreased consumption of resources. The developers, financiers and media boosters of this city argue for a speculative space ahead of its time that operates at the synaptic level of its inhabitants.

Q) How pleasant and acceptable would be this vision of management of life with high-end monitoring devices? Will it be efficient or suffocating? Where does all this monitored data go and how are the decisions made? What will be the effects of a totalizing sensory environment on the interactions of citizens and what kind of decisions will be deduced from that data?

For example, marketing videos showed the roll-out of tele-medicine applications, which required, as some engineers suggested, transforming the laws of South Korea to allow the construction of medical grade networks to allow genetic and other data to flow from labs in the home to medical sites in the proliferation of house health-care services.

Q) What could be the implications and how would it alter the decisions that could possibly use this information? Who would be responsible for the protection of this data from being hacked and misused? How transparent will the system be and would citizens know how this data flows and its effects on their interactions in routine activities?

The promise of such number-crunching is that we will learn previously unknown things about ourselves based on an idea that the collective behavior of a city can be compiled and analyzed by machines in order to reveal profound trends in our social behavior. However, this approach could also easily, and perhaps dangerously, produce a number of false correlations.

Q) What would be the validation mechanism for these trends? What are some of the visualized outcomes? What would be the cost, cities, and citizens pay to try this methodology in the desire of an outcome that promises fitting complex urban functions and city dynamics in a numerical representation of trends? What could be some possible false correlations? What would be a mechanism to identify and filter these correlations? What could be the implications of not being able to identify these correlations and how would it effect the decision-making.

Quantified Community: Hudson Yards

Technoscientific urbanism reflects a neo-positivist return to postwar systems thinking and centralized planning; it is especially visible in the discourse around “smart cities”, which regards the intelligence generated from spatial sensing and data analysis as a “fix” for perennial urban problems.

Q) Can spatial sensing and data analysis result in a quality based decision making? What would be the process to identify the urban problems that need a fix by analyzing numbers? Would this methodology give rise to more unspeculated urban problems which would need another version of smart cities to deal with them? Will this versioning be an ever going process, not of evolving but of switching from one methodology to another giving rise to new problems in an attempt to solve old ones?

Hudson Yards offers the first opportunity in the United States to build, from the ground up, sharing”the most connected, measured, and technologically advanced digital district in the nation.”

Songdo city is built on the vision of a networked community, connecting the unconnected, real-time data analytics and spatial sensing on urban landscape.

Q) Most of all the smart city visions seem to share a common ground in terms of their philosophy of using big data and connecting communities as the primary solution for every urban problem. Where did this idea seed from? Is there no alternate way of constructing a smart city other than weaving it with networks and digital technologies?

Are there opportunities for meaningful citizen participation in creating the smart technologies that will define Hudson Yards.

Q) Who do we mean by meaningful citizen participation? What counts as meaningful? And at what cost? To what extent will it demand a compromise to privacy? Will the participation be a choice? How does that behave in the concept of geosurveillance and what could be the outcome of participation? Will it lead to social sorting, predictive profiling? Will the system be transparent to understand how the data from participation is used and how it affects the process of decision making?

Urban data Infrastructures

“Smart cities and the politics of urban data,” Smart Urbanism: Utopian Vision or False Dawn

To be smart that is to act with wisdom one requires knowledge, which is dependent on information, which is extracted from data.

Where data itself is a process of constraints and choices, and cannot be seen as neutral but as situated, contingent, relational and framed, the process of data analysis is much more complex.

Q) The relationship of smartness, wisdom, knowledge, information and data is a complex process. The transition of data to wisdom to smartness is not a straightforward mathematical computation and thus it is crucial to understand, who are the entities that process this data to transition it from information to knowledge? What are the parameters that define this transition? What is the framework for the same and who controls, monitors, participates or contributes to the functioning mechanisms of this framework?

Panoptic surveillance, predictive profiling, and social sorting.

The fear is that, far from being a liberatory and empowering development, smart cities may lead to highly controlling and unequal societies in which the rights of privacy, confidentiality, freedom of expression and life chances are restricted.

Q) If this happens to be a right speculation for the smart city vision, it is important to understand the role of citizens in this scenario. Will this shift be so subtle leaving citizens unable to realize it or will it be imposed in a sudden explicit format? Will there be a resistance from the citizens or will it leave them unable to identify the transition until it becomes unavoidable to reject?

Facts are produced, not simply measured.

Q) The context in which big data is collected, analyzed and presented defines the decision-making. Who are the power structures that define this process of gathering data, marking for data analysis and the format for data presentation? What would be the new strategies crafted around these facts? What form of governance will it give rise to?