Thao Phan

This commentary uses Paul Gilroy's controversial claim that new technoscientific processes are instituting an 'end to race' as a provocation to discuss the epistemological transformation of race in algorithmic culture. We situate Gilroy's provocation within the context of an abolitionist agenda against racial-thinking, underscoring the relationship between his post-race polemic and a post-visual discourse. We then discuss the challenges of studying race within regimes of computation, which rely on structures that are, for the most part, opaque; in particular, 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. We argue that in this new regime, race emerges as an epiphenomenon of processes of classifying and sortingwhat we call 'racial formations as data formations'. This discussion is significant because it raises new theoretical, methodological and political questions for scholars of media and critical algorithmic studies. It asks: how are we supposed to think, to identify and to confront race and racialisation when they vanish into algorithmic systems that are beyond our perception? What becomes of racial formations in post-visual regimes?

Between 2016 and 2020, Facebook allowed advertisers in the United States to target their advertisements using three broad ‘ethnic affinity’ categories: African American, U.S.-Hispanic, and Asian American. Superficially, these categories were supposed to allow advertisers to target demographic groups without using data about users’ race, which Facebook explicitly does not collect. This article uses the life and death of Facebook’s ‘ethnic affinity’ categories to argue that they exemplify a novel mode of racialisation made possible by machine learning techniques.

Adopting Wendy H. K. Chun’s conceptualisation of race ‘and/as’ technology as an analytical frame, this article focuses on what ‘ethic affinity’ categories do with race. ‘Ethhnic affinity’worked by analysing users’ preferences and behaviour: they were supposed to capture an ‘affinity’ for a broad demographic group, rather than registering membership of that group. That is, they were supposed to allow advertisers to ‘personalise’ content for users depending on behaviourally determined affinities. We argue that, in effect, Facebook’s ethnic affinity categories were supposed to operationalise a ‘post-racial’ mode of categorising users. But the paradox of personalisation is that in order to apprehend users as individuals, platforms must first assemble them into groups based on their likenesses with other individuals.

Even in the absence of data on a user’s race—even after the demise of the categories themselves—users can still be subject to techniques of inclusion or exclusion for discriminatory ends. The inductive machine learning techniques that platforms like Facebook employ to classify users generate proxies, like racialised preferences or language use, as racialising substitutes. We conclude that Facebook’s ethnic affinity categories in fact typify novel modes of racialisation that are often elided by the claim that using complex machine learning techniques to attend to our preferences will inaugurate a post-racial present. Discrimination is not personalisation’s accidental product; it is its very condition of possibility. Like that of Facebook’s ethnic affinity categories, its death has been greatly exaggerated.

Overington, C. & Phan, T. (2016). Domesticating drone technologies: Commercialisation, banalisation, and reconfiguration of ‘ways of seeing’. In R. Tippet & H. Randall-Moon (ed.) Security, race, biopower: Essays on technology and corporeality. Sydney: Palgrave Macmillon

The production of the #cokedrone YouTube advertisement by Coca-Cola Singapore in 2014 is a manifestation of the broader trend toward the domestication of drone technologies within city spaces, indicating a prolonged desire to eschew its relationship to violence. This article seeks to briefly provide one interpretation into this ad and the broader contextual implications of drones in cities. We argue that while a variety of strategies are clearly deployed within this ad—the redesign of the body of the drone, the attempt to negate the relation between drones and violence, and finally, through the reconfiguration of the drone eye from the eye that ‘watches’ to the eye that ‘sees’—the overall implications of drone technologies within city spaces warrants further investigation. Particularly as drone technologies are easily adaptable to changing environments, often concealing its security and surveillance capabilities, commercial and domestic participants in this trend must be critically aware of the potential consequences underlying the normalisation of drones as part of everyday life in the city.