Unsupervised by any other name: Hidden layers of knowledge production in artificial intelligence on social media

TitleUnsupervised by any other name: Hidden layers of knowledge production in artificial intelligence on social media
Publication TypeJournal Article
AuthorsBechmann, Anja, and Geoffrey C. Bowker
JournalBig Data & Society
Volume6
Issue1
Pagination2053951718819569
ISSN2053-9517
AbstractArtificial Intelligence (AI) in the form of different machine learning models is applied to Big Data as a way to turn data into valuable knowledge. The rhetoric is that ensuing predictions work well—with a high degree of autonomy and automation. We argue that we need to analyze the process of applying machine learning in depth and highlight at what point human knowledge production takes place in seemingly autonomous work. This article reintroduces classification theory as an important framework for understanding such seemingly invisible knowledge production in the machine learning development and design processes. We suggest a framework for studying such classification closely tied to different steps in the work process and exemplify the framework on two experiments with machine learning applied to Facebook data from one of our labs. By doing so we demonstrate ways in which classification and potential discrimination take place in even seemingly unsupervised and autonomous models. Moving away from concepts of non-supervision and autonomy enable us to understand the underlying classificatory dispositifs in the work process and that this form of analysis constitutes a first step towards governance of artificial intelligence.
URLhttps://doi.org/10.1177/2053951718819569
DOI10.1177/2053951718819569
Short TitleUnsupervised by any other name
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