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Algorithmic Decision-Making: Disputes and Contradictions in the American Context

Student: Dmitriy Muravyov

Supervisor: Polina Kolozaridi

Faculty: Faculty of Social Sciences

Educational Programme: Political Science (Bachelor)

Year of Graduation: 2020

In this thesis, I examine the existing approaches to problematizing algorithmic decision-making politically. Despite the growing political significance of algorithms in public policy and in civic life, little research has so far paid attention to the political status of algorithmic systems in relation to their decision-making capacities. In this work, I intend to contribute to this understanding. Firstly, I map approaches to understanding algorithmic systems by looking at specific concepts that are important in discussing this issue. Secondly, I trace the history of the relationship between academia, government, and industry in the US context by paying specific attention to how the understanding of algorithmic systems has been changing. Thirdly, I theorize the politics and critique of algorithms to chart more productive ways to engage in the transformation of algorithmic systems politically.

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