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big data and the politics of austerity 

From Infoglut, by Mark Andrejevic, loc 607. The context to digital innovation in public services: 

What emerges is a kind of actuarial model of crime: one that lends itself to aggregate considerations regarding how best to allocate resources under conditions of scarcity – a set of concerns that fits neatly with the conjunction of generalized threat and the constriction of public- sector funding. The algorithm promises not simply to capitalize on new information technology and the data it generates, but simultaneously to address reductions in public resources. The challenges posed by reduced manpower can be countered (allegedly) by more information. As in other realms, enhanced information processing promises to make the business of policing and security more efficient and effective. However, it does so according to new surveillance imperatives, including the guidance of targeted surveillance by comprehensive monitoring, the privileging of prediction over explanation (or causality), and new forms of informational asymmetry. The data- driven promise of prediction, in other words, relies upon significant shifts in cultures and practices of information collection.

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