10. Marginalised Geographies and Spatialised Identities

Many cities now collect, aggregate and oftentimes visualise data to identify neighbourhoods in need of greater policing, public assistance or restructuring. And the rhetoric about these initiatives usually includes claims that the use of digital technologies, social media platforms, and collected data will make city officials more accountable, enable greater citizen input, and improve the overall quality of urban life. As this chapter argues, however, many of these practices function to aggravate already existing racial–spatial divisions, construct and reinforce existing topologies of power, and deleteriously mediate and threaten neighbourhood identities. Specifically, this chapter investigates data-driven constructions of geographic knowledge and state power, particularly as manifested through certain affective technologies of safety and security, such as crowdsourcing smartphone applications, the digital visualisation of crime, and the more recent phenomenon of predictive policing. Relying in part on Richard Grusin’s theory of premediation, I argue that the more recent and growing phenomenon of predictive policing, wherein cities use data to help predict future crimes, tends to target lower class neighbourhoods and functions to premediate and reinforce existing socio-economic disparities. Similarly, citizen-sourcing smartphone apps that encourage residents to report problems in their neighbourhoods may allow for greater agency and citizen engagement, on the one hand, but also become indicative of neoliberal techniques that shape productive, autonomous, and self-regulating citizens and ordered socio-spatial constructs.