Loops, ladders and links: the recursivity of social and machine learning
Marion Fourcade1, Fleur Johns2
1Department of Sociology, University of California Berkeley, 410 Barrows Hall, Berkeley, CA 94720-1980 USA.
Abstract:
Machine learning algorithms reshape how people communicate, exchange, and associate; how institutions sort them and slot them into social positions; and how they experience life, down to the most ordinary and intimate aspects. In this article, we draw on examples from the field of social media to review the commonalities, interactions, and contradictions between the dispositions of people and those of machines as they learn from and make sense of each other.
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