Toward a Minor Tech:Toward a Minor Tech:Crichlow 500

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Scaling Up, Scaling Down: Racialism in the Age of ‘Big Data’

Camille Crichlow

Breaking the surface of skin and enveloping the racial body politic in ever-minute scales of perceptual closeness, the genomic revolution of the 1990’s gestured toward racialism’s still potential demise: the end of race itself. As older conceptions of race explicitly tied to anatomical scales of the body were belied by a breakthrough consensus – that race has no fundamental basis in human biology – the perceptual regimes to which racialism was attached were, as sociologist Paul Gilroy claims, ambivalently undone (1998).

In the context of 21st century digital processing, another break in racial scale has emerged. There is a sense that race is being remade not within extant contours of the body’s visibility, but outside corporeal recognition altogether. Predictive policing, for example, increasingly relies on an accumulation of data to construct zones of suspicion through which the racial body is interrogated (Brayne 2020; Chun 2021). While racial categories are not explicitly coded within the classificatory techniques of analytic technologies, large-scale automated data processing condense and map racialising outputs that, without critical interrogation, appear neutral. Thao Than and Scott Wark define these algorithmically generated racial formations as ‘data formations’: “modes of classification that operate through proxies and abstractions and that figure racialized bodies not as single, coherent subjects, but as shifting clusters of data” (1, 2020).

As large-scale automated data processing reproduces patterns of racialisation indiscernible to the human eye, the question of scale has again become relevant to a post-visual discourse of race. What if the historical compression of racial scale—a movement of race-craft inwards and downwards into the minute and microscopic signifiers of the body — now exerts upwards and outwards pressures into a globalised regime of datafication? In other words, how is racial epistemology reproduced, reconstructed, and reified within the scalar magnitude of ‘big data’? These questions are not to suggest that racialism as it has been historically constituted is being dismantled by the grand scale of computational processing; or that other modes of racialist discourse are not still firmly rooted within material experience. Rather, I reference the loosening of race from the grips of not only ocular modes of seeing, but perceptual regimes of racial scale, whereby race category is not only assigned to the small-scall signifiers of the body, but inferred through large-scale algorithmic correlation, categorisation, and abstraction of data. While racialisation and data have always been constitutive (Womack 2021; Zuberi 2001), the scale of ‘big data’ mask an insidious realignment whereby race seems to disappear, while its effects are more deeply inscribed within lived experience.

Yet, racialisation is not overdetermined by large-scale automated data processing. Beyond ‘opting out’ of data regimes or obfuscating oneself from surveillance apparatuses, possibilities of transfiguration that refuse racialising and colonialist ‘data relations’ remain conceivable (Couldry and Mejias). This begins with refusing the absolute neutrality that ‘big data’ regimes attempt to guarantee. How might ‘big’ and ‘small’ tech be mobilised towards liberatory practices of refusal that challenge scalar realignments of racialism, and transform domains of experience toward an end of race futurity?