The Everyday of Future-Avoiding: Data-drivenness and Administering the Smart City

Authors: Leah Horgan*, UC Irvine, Paul Dourish, UC Irvine
Topics: Urban and Regional Planning, Urban Geography
Keywords: data-driven governance; big data; governance; smart cities
Session Type: Paper
Day: 4/5/2019
Start / End Time: 9:55 AM / 11:35 AM
Room: Washington 3, Marriott, Exhibition Level
Presentation File: No File Uploaded

Smart cities are animated by the promise of big data to manifest optimal futures. Here, disparate mathematical, analytical, and predictive techniques utilize data derived from the citywide sensor networks, and other surveillance infrastructure such as drones and satellite imaging. While much is made of using these often profit-driven tools to secure best possible futures, we find that the everyday of administering the smart city is instead coiled around logics of risk and prevention. Cities are cash-strapped and beholden to a new managerialism that requires intensive regimes of cost-effectiveness, efficiency, and transparency. City officials are under increased scrutiny to ensure errors, waste, and accidents are avoided, and new smart cities tools are put to work in this vein. We draw on two years of ethnographic work with a civic data team in a major West Coast city to explore how logics of prevention are operationalized in “smart” city administration. Civil service is altered in the course of these configurations. We center on three areas: law enforcement, traffic control, and emergency management. As Masco (2015) has demonstrated, impossible administrative commitments such as preventing all harm “fuse the problem of futures, infrastructures, expertise, and international competition with affect in a new way.” Additionally, these affective global logics—that suspend certain peoples, locales, and scenarios into categories of risk (Beck 1999)—are now being determined algorithmically (e.g. predictive policing). We look at everyday use of data technologies, and the agentic ideals undergirding them, to examine increased datafication as justified through logics of prevention.

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