Illegible data: A counterpoint to the evidence-based approach in policy decision making

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University of the Witwatersrand, Johannesburg
The art of governing is closely linked to the statecraft of decision making based on evidence. Population dynamics, social change and the growth of the middle class are some of the data analyses used to shape and influence policy directions and programmatic interventions in particular places. Data analysis is a crucial technology of governance, and it is how place, people and neighbourhoods are known and made legible to the state where the typical goal of the state is the reduction of the ‘disorderly, constantly changing social reality beneath it to something more closely resembling the administrative grid of its observations’ (Scott, 1998:82). Moreover, this ordering tendency is necessary for decision making that will have the highest impact for the greatest number of people – so there is, indeed, a crucial logic to this approach. Drawing from feminist urban scholars and others, this paper offers a provocation of sorts. It discusses the implications of the homogenising tendency at the heart of data-led approaches to governing. It considers the categories of urban residents and urban life that evade simplification and thus escape meaningful inclusion in policy intervention. This paper does not provoke a discussion of the ‘residual/elided/invisible/foreclosed’, that is, the illegible, unreadable and unseen in an attempt to diminish the potential and power of data-driven approaches to governance. Rather, it offers a counterpoint, and argues for the other kinds of illegible/unseen/residual data to sit alongside the data considered more legible and credible for decision-making processes. The goal of doing this is so that our knowing, official interests and rational models of policy intervention do not become mechanised or automated, but retain a view on the textual, nuanced and unresolved matters that make up everyday life in everyday contexts.
African Governance, Digital Age, Illegible data, Homogenising tendency, Data-driven approaches to governance, Art of governing