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Journal article
Epistemic welfare and public service media's algorithmic recommender systems: A theoretical framework, operationalization and relevance for governance
European journal of communication (London), Forthcoming
28 Oct 2025
Abstract
This contribution introduces the comprehensive framework of epistemic welfare to discuss how public service media (PSM) can engage with algorithmic recommender systems in a manner in keeping with PSM's foundational principles. We contextualize PSM algorithmic recommenders in their tradition of content curation and discuss the challenges PSM face in implementing these systems. We introduce epistemic welfare, a framework based in social epistemology and welfare studies, defined as concerned with creating and maintaining conditions and capabilities for epistemic agency of citizens in the public sphere. We discuss the epistemic standards of reliability, power, fecundity, speed, and efficiency and illustrate the framework's operationalization for the design and implementation of recommenders and its relevance for governance by and of PSM's algorithms. Ensuring that algorithmic recommender systems fit epistemic welfare, we argue, allows PSM to help tackle the epistemic disruptions in the digitalized public sphere.
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Details
- Title
- Epistemic welfare and public service media's algorithmic recommender systems: A theoretical framework, operationalization and relevance for governance
- Creators
- Hilde Van den Bulck - Drexel UniversityMichelle Kulig - University of FribourgAaron Hyzen (Corresponding Author) - University of AntwerpManuel Puppis - University of FribourgSteve Paulussen - University of Antwerp
- Publication Details
- European journal of communication (London), Forthcoming
- Publisher
- SAGE Publications
- Number of pages
- 21
- Grant note
- Drexel AEO Pilot Award: 284279 Fonds Wetenschappelijk Onderzoek Vlaanderen (FWO): G078625N Swiss National Science Foundation Switzerland (SNSF): 100019E_212521
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project was funded by Drexel AEO Pilot Award (project 284279), Fonds Wetenschappelijk Onderzoek Vlaanderen (FWO project G078625N), and Swiss National Science Foundation Switzerland (SNSF project 100019E_212521).
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Communication
- Web of Science ID
- WOS:001603269500001
- Scopus ID
- 2-s2.0-105019952712
- Other Identifier
- 991022124362304721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Communication