Data Vision: Learning to See Through Algorithmic Abstraction

Learning to see through data is central to contemporary forms of algorithmic knowledge production. While often represented as a mechanical application of rules, making algorithms work with data requires a great deal of situated work. This paper examines how the often-divergent demands of mechanizati...

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Veröffentlicht in:	arXiv.org 2020-02
Hauptverfasser:	Passi, Samir, Jackson, Steven J
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Computer Science - Computers and Society Computer Science - Human-Computer Interaction Computer Science - Learning Contingency Data analysis Decision analysis Empirical analysis Knowledge representation Machine learning Mathematical analysis Mechanization Statistics - Machine Learning Vision
Online-Zugang:	Volltext
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