Data Ableism: Ability Expectations and Marginalization in Automated Societies

Abstract

While data is increasingly proffered as the resource that unlocks the promises of the digitalized world, for underprivileged individuals and communities, instead of fulfilled promises, datafication means additional marginalization. Examining these forms of marginalization, this article considers how technological advancements come with ability expectations, and highlights the exclusion and discrimination of disadvantaged segments of the population that result from failing to meet digital ability expectations and reach prescribed data norms. Drawing from critical disability scholarship, we introduce the notions of data ableism and data disablism, which encapsulate privileged ability expectations pertaining to data production and the resulting forms of exclusion that are prevalent in automated societies. Underlining the intersectional nature of data ableism, we discern its two main mechanisms, namely data (in)visibility and data (un)desirability, and document the role of free market ideology in producing and upholding data ableism.