University of Calgary
sava saheli singh
University of Ottawa
From wearables, IoT sensors, apps, platforms and cameras, we “shed” various forms of data as we navigate our increasingly networked and smart environments. Recent discussions of urban data have focused on post collection practices of translation and circulation – following data threads, journeys and exhaust as they enact urban life. We seek to further complicate these thick data accounts focusing on movement, bodies and embodiment. As our bodies become information, the accuracy and affordances of these data portraits remain critical sites of inquiry. How do surveillance technologies, map, render and perform human and non-human interactions; moreover, exacerbate injustice? In this paper, adding to the rich discussions of future-ing, anticipatory imaginaries and implications on the urbanite body, we offer a critical interrogation of the oligoptic gaze and the relations and politics of visibility. We do this through the narrative of Frames [https://www.sscqueens.org/projects/screening-surveillance/frames] – a speculative near future account of mapping a body through the various lenses of a smart city. Focused on what is included (and excluded) from the “frame”, we navigate domains of aesthetics and politics in order to foreground the embodied experiences, decisions and interactions which are mapped by these surveillant spatial locative technologies. We contend these renderings or simulacra of a ‘singular’ knowledge politic serve to stabilize and normalize ways of seeing, knowing and control. Yet, these rationalities are irrational – potentially producing inefficient, inaccurate and unjust portraits.
This paper takes up synthetic populations as a way to discuss the ethics of uncertainty in data-driven urban processes. Urban-tech tells us that better data is a replacement for more robust democracy; that urban issues are solved through more computation, not more deliberation; and that data can increasingly substitute for political representation. In the face of these ever louder claims for calculable urban futures we examine the logics underlying one of these urban models conceptually and methodologically. Synthetic populations describe a fictitious but statistically representative urban populace. Materially, a synthetic population is a dataset. A dataset comprised of individual-level statistics, (think of age, household income, number of children) which were calculated from aggregate data, for example, the number of 35-40 year olds per census tract. Thus, population synthesis is a method that aims to generate granular data where it didn’t exist previously, a way of estimating specificity. These fictional populations are mobilized in the form of computational depictions of human behavior and decisions in ‘agent-based models’. Synthetic urban residents are used to determine the impacts of transportation systems; to map the spread of disease; and to draw segregation over time; to inform urban policy. This paper presents ongoing research using GIS-based methods to investigate whether synthetic populations evenly represent the cities and citizens they claim to describe. It asks whether mathematical sophistication here obscures an underlying uncertainty, and, in turn, speculates on the stakes of this uncertainty for the creation of a just city.