Leszczynski argues that besides the common understanding of big data and urban governance as tools for real-time management in smart cities, it is also essential to consider using big urban data in algorithmic governance to control undesirable urban futures. This approach prioritises security over efficiency and relies on the abstraction of individuals into decontextualised encodings that serve as functional inputs for speculative calculi that anticipate particular kinds of subjects.
The “urban derivative” concept is introduced to understand how individuals and the city are positioned within this mode of algorithmic governance. Microsoft’s Pedestrian Route Production service is an example of how normative, risk-averse neoliberal subjects are assumed to self-securitise by adopting and utilising the service to mitigate any threats to their safety associated with walking through “unsafe” neighbourhoods.
The article also discusses the use of user-generated content from social media in preemptive urban securitisation, such as the EMOTIVE platform for generating real-time “mood maps” of UK cities. This approach relies on the continuous flow of non-curated data from social media and is designed for state actors such as urban law enforcement. The operationalisation of this approach is entirely dependent on the presence of public entities such as social media companies, whose products generate flows of content made available to third parties through the shared use of their APIs.
Leszczynski states that big data security is anticipatory in scope, relying on the speculation of data-driven futures assembled across content flows and rendered actionable in the present. This approach is a defining feature of emergent modes of state-enacted signals intelligence activities crystallising around big data.
The conclusion is that the interplay between efficiency and security in urban algorithmic governance is complex and mutually implicated. The urban derivative is a valuable concept for understanding how urban management is transformed by using big data and algorithmic governance to anticipate and control future urban scenarios.
Bibliography:
Leszczynski, A. (2016). Speculative futures: Cities, data, and governance beyond smart urbanism. Environment and Planning A: Economy and Space, 48(9), 1691–1708. https://doi-org.ezproxy.brighton.ac.uk/10.1177/0308518X16651445