Affiliation:
1. School of Politics and International Relations, Queen Mary University of London, London, UK
Abstract
Part of an accelerated trend to integrate algorithms in immigration decision-making, the UK's EU Settlement Scheme relies on automated data checks as an essential and mandatory step in the application for UK residence. In this article, I engage with the literature on datafication and algorithmic accuracy to showcase algorithmic inaccuracy within borders in regard to the allocation of residence statuses and rights. I argue that, while the EUSS uses big data to create a data double of the ‘desirable’ migrant, even applicants within this category experience mismatches. Some EU+ Citizens on linear residence and career trajectories were initially offered pre-settled status and had difficulty proving their entitlement to the full status, while others, who did not qualify for settled status, obtained it nevertheless. The analysis is based on in-depth interviews with high skilled applicants, and experts on the EUSS, exposing that footprints are not evidence per se. Instead, the outcomes are decided by an opaque algorithm that is not retained and disappears as easily as footprints in quicksand.
Cited by
1 articles.
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