Speculative futures: Cities, data, and governance beyond smart urbanism

Agnieszka Leszczynski

Environment and Planning A, 2016, vol. 48, issue 9, 1691-1708

Abstract: In this paper, I examine the convergence of big data and urban governance beyond the discursive and material contexts of the smart city. I argue that in addition to understanding the intensifying relationship between data, cities, and governance in terms of regimes of automated management and coordination in ‘actually existing’ smart cities, we should further engage with urban algorithmic governance and governmentality as material-discursive projects of future-ing, i.e., of anticipating particular kinds of cities-to-come. As urban big data looks to the future, it does so through the lens of an anticipatory security calculus fixated on identifying and diverting risks of urban anarchy and personal harm against which life in cities must be securitized. I suggest that such modes of algorithmic speculation are discernible at two scales of urban big data praxis: the scale of the body, and that of the city itself. At the level of the urbanite body, I use the selective example of mobile neighborhood safety apps to demonstrate how algorithmic governmentality enacts digital mediations of individual mobilities by routing individuals around ‘unsafe’ parts of the city in the interests of technologically ameliorating the risks of urban encounter. At the scale of the city, amongst other empirical examples, sentiment analytics approaches prefigure ephemeral spatialities of civic strife by aggregating and mapping individual emotions distilled from unstructured real-time content flows (such as Tweets). In both of these instances, the urban futures anticipated by the urban ‘big data security assemblage’ are highly uneven, as data and algorithms cannot divest themselves of urban inequalities and the persistence of their geographies.

Keywords: Algorithmic governance; big data; future; security; smart cities (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:sae:envira:v:48:y:2016:i:9:p:1691-1708

DOI: 10.1177/0308518X16651445

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