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  • 2015 art exhibit by Danilo Correale called “The Missing Hour: Rhythms and Algorithms”.
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Collaborative Filtering and Personal Identity: A Conversation on the Artificial-Intelligences of Streaming Platforms, 2020.

Collaborative Filtering is an algorithm application which predicts the tastes and desires of consumers. Often presented as “Recommended for you” and “Discover weekly” on streaming platforms— collaborative filtering is a highly utilized tool streaming platforms use to dictate their consumer’s aesthetic engagements. This highly effective technology provides social theory and philosophy with a situation of ambiguity due to its fast-paced public delivery and covert methods. To help accurately diagnose the motivations of an A.I metric-driven Western entertainment industry, this paper researches and analyzes some of the hidden infrastructures of streaming platforms' use of collaborative filtering. This paper hopes to introduce some concepts in Critical Theory in order to analyze how these types of algorithms of decision making affect personal identity.

Benjamin Micallef
B.A. Comparative Literature, Philosophy | UC Berkeley Literature |
My name is Benjamin Micallef and my undergraduate experience has led me the topic of critical theory. Everyday I am reading more and more on social psychology, public affairs, class consciousness and Marxism. I plan on implementing my liberal arts education in the music and entertainment industries, where they intersect with social movement and ideology. I am also an NCAA student athlete on the Cross Country and Track Team.

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PAPER FINAL_ Collaborative Filtering and Personal Identity.docx (5.22 MB)

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