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Cultural Policies, Social Missions, Algorithms and Discretion: What Should Public Service Institutions Recommend?

Part of the Lecture Notes in Computer Science book series (LNISA,volume 12051)


Digital media services, and streaming services in particular, filter and recommend content to their users by the use of algorithms. In this paper, we ask what happens when institutions like public service broadcasters, public libraries, as well as other media institutions who base their operations on public funding and social mission statements, implement similar algorithms. Can we think of alternate algorithmic principles? What should public service algorithms recommend, who would decide, and based on what criteria? In order to address questions such as these, we argue for a broad approach based on not only technological considerations, but also complementing perspectives touching upon how such institutions are situated in the media industries, relevant cultural policy frameworks and practices for handling quality assessments. Using examples from Scandinavian public service and media institutions, we indicate how the coding of algorithms have profound social and cultural implications. This short paper thus initiates a project with the aim of examining various algorithmic perspectives that could - and perhaps should - be taken into account when approaching issues of cultural policies, social missions and discretion in publicly funded culture institutions.


  • Social missions
  • Public service
  • Recommender systems

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Correspondence to Kim Tallerås .

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Tallerås, K., Colbjørnsen, T., Oterholm, K., Larsen, H. (2020). Cultural Policies, Social Missions, Algorithms and Discretion: What Should Public Service Institutions Recommend?. In: Sundqvist, A., Berget, G., Nolin, J., Skjerdingstad, K. (eds) Sustainable Digital Communities. iConference 2020. Lecture Notes in Computer Science(), vol 12051. Springer, Cham.

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  • Print ISBN: 978-3-030-43686-5

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