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  1. Can an Algorithm be Agonistic? Ten Scenes from Life in Calculated Publics.Kate Crawford - 2016 - Science, Technology, and Human Values 41 (1):77-92.
    This paper explores how political theory may help us map algorithmic logics against different visions of the political. Drawing on Chantal Mouffe’s theories of agonistic pluralism, this paper depicts algorithms in public life in ten distinct scenes, in order to ask the question, what kinds of politics do they instantiate? Algorithms are working within highly contested online spaces of public discourse, such as YouTube and Facebook, where incompatible perspectives coexist. Yet algorithms are designed to produce clear “winners” from information contests, (...)
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  • How the machine ‘thinks’: Understanding opacity in machine learning algorithms.Jenna Burrell - 2016 - Big Data and Society 3 (1):205395171562251.
    This article considers the issue of opacity as a problem for socially consequential mechanisms of classification and ranking, such as spam filters, credit card fraud detection, search engines, news trends, market segmentation and advertising, insurance or loan qualification, and credit scoring. These mechanisms of classification all frequently rely on computational algorithms, and in many cases on machine learning algorithms to do this work. In this article, I draw a distinction between three forms of opacity: opacity as intentional corporate or state (...)
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