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.
This paper draws on a mapping project, C19LatinoNYC.org, that I have been conducting with students in introductory Latinx literature courses, which involves plotting addresses found in archival sources to recover the understudied community of writers, editors, printers, booksellers, who once led New York’s nineteenth-century Latinx press. I consider digital mapping as a research and pedagogical tool for confronting absences in the archive and for making history not just knowable, but also teachable in new ways that enable students to critique and confront structural inequality and systematic oppression. I argue that digital mapping provides a means of realizing the potential of our digitally dominated media system to put the past in conversation with current struggles for social justice. This paper speaks to those who research and teach courses in Latinx Studies. It is also meant to spark interdisciplinary conversation, especially among those working in fields that must confront absences and omissions in the archive, including hemispheric studies, black Atlantic studies, and indigenous studies.
Mississippi State University
This paper asks, and seeks to answer, the question: what makes mapping critical? I argue that most examples of ‘doing’ critical mapping tend to fall into one of two camps with very different manifestations, goals and assumptions. The first of these groups takes inspiration from Donna Haraway’s invocation of – and desire to counteract – what she calls the ‘god trick’ of ostensible technoscientific objectivity, reworking the map in order to challenge its privileged epistemological position. The second group seeks to leverage the ostensible objectivity of maps and quantitative data to prove the existence of social inequality in the spirit of what the geographer Elvin Wyly has called ‘strategic positivism’. The rest of the paper argues, however, that these two positions are not mutually exclusive, and that practitioners of critical mapping need not choose between the twin imperatives of stabilizing our understanding of the objectivity of cartographic knowledge and taking advantage of such a pervasive understanding in order to produce more just social and spatial outcomes. It is possible to simultaneously use maps to prove that inequality exists and that space matters, while also demonstrating that the ways we conventionally think about space through maps aren’t really sufficient to understand what’s actually going on in the world. Using examples from my own research on mapping the relational geographies of concentrated poverty and affluence in Lexington, Kentucky, I demonstrate one possible example of what such an approach to situated mapping might look like.
Craig M. Dalton
University of Washington-Tacoma
Data is the lifeblood of mapping. Without it, even the most rhetorically powerful lacks substance. Recent counter-mapping by groups like the Anti-Eviction Mapping Project and Argentina’s Iconoclasistas reveal how data can be powerfully repurposed in the right setting. In contrast, personal location data, whether big data or data science, tends to be the tool of major corporations and governmental initiatives, from Facebook to Google, the New York Police Department to the Chinese social credit system. Popular media suggest that people have little input or ability to influence how they are mapped and profiled, and subsequently advertised to or their movements blocked. In this paper, we seek to survey how people actively and passively resist and/or shape the collection and use of their personal location information, a form of everyday counter-mapping, as people attempt to exert influence over their data. We develop a typology of strategies of how people engage the production and use of their personal geographic data: acceptance, active resistance, making present, and escape. By identifying and cohesively conceptualizing such strategies, we aim to develop a series of approaches to exert more control over spatial data about oneself. We focus on strategies for two reasons. First, modes of resistance are highly contextual in terms of the political and social processes at work. Second, discrete technical efforts, such as turning off your phone’s GPS or using a VPN, can be quickly rendered obsolete or circumvented as technologies change in the continuing arms race of privacy and data capitalism. The strategies we hope to shed light on can adapt their specific implementations, remaining relevant and useful as conditions shift.