The Whiteness of AI

By Stephen Cave, Kanta Dihal. 2020

211 citations recorded by the source corpus.

This paper focuses on the fact that AI is predominantly portrayed as white—in colour, ethnicity, or both. We first illustrate the prevalent Whiteness of real and imagined intelligent machines in four categories: humanoid robots, chatbots and virtual assistants, stock images of AI, and portrayals of AI in film and television. We then offer three interpretations of the Whiteness of AI, drawing on critical race theory, particularly the idea of the White racial frame. First, we examine the extent to which this Whiteness might simply reflect the predominantly White milieus from which these artefacts arise. Second, we argue that to imagine machines that are intelligent, professional, or powerful is to imagine White machines because the White racial frame ascribes these attributes predominantly to White people. Third, we argue that AI racialised as White allows for a full erasure of people of colour from the White utopian imaginary. Finally, we examine potential consequences of the racialisation of AI, arguing it could exacerbate bias and misdirect concern.

Subfields: Gender Studies, Sociology and Political Science

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Citations in the corpus

Taxonomy of Risks posed by Language Models (2022, background): “Non-linguistic AI systems were found to typically present as ‘intelligent, professional, or powerful’ and as ethnically White, reinforcing historical racist associations between intelligence and whiteness [35].”
Towards Measuring the Representation of Subjective Global Opinions in Language Models (2023, unknown): “…it risks imposing potentially undesirable effects such as promoting hegemonic worldviews and homogenizing people’s perspectives and beliefs (Barocas & Selbst, 2016; McConnell-Ginet, 2020; Gabriel, 2020; Cave & Dihal, 2020; Weidinger et al., 2021; 2022; Bommasani et al., 2022; Jakesch et al., 2023).”
Mirages: On Anthropomorphism in Dialogue Systems (2023, background): “Though intelligence and understanding should not be conﬂated with systems that exhibit humanlike behaviour (Bender and Koller, 2020), the human tendency to anthro-pomorphise convinces us of a machine’s apparent intelligence (Proudfoot, 2011).”