aau_ub/ouschanDemocratic algorithms: ethnography of a public recommender system
Nikolaus Poechhacker
In his book, Nikolaus Poechhacker reconstructs the making of an ML powered recommender system in public broadcasting (PBS). These days media consumption is highly mediated by algorithmic systems, e.g. on platforms like YouTube or Netflix, which filter out relevant information for the users from an abundant information space. These systems have been criticized, as they can create filter bubbles. PBS, however, faces the issue that it ought to implement these technologies, as they have become a standard cultural technique, but at the same time have to present a wide variety of information that follows the principle of diversity. The ethnographic study told in “Democratic Algorithms” discusses the difficulties of implementing a public service recommender algorithm on the technical, the organizational, and political level.
The book also presents a new way how to think about algorithmic systems and how to design them along the normative and legal categories of our democratic societies.
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