Journal article
Knowledge silos as a barrier to responsible AI practices in journalism? Exploratory evidence from four Dutch news organisations
- Abstract:
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The effective adoption of responsible AI practices in journalism requires a concerted effort to bridge different perspectives, including technological, editorial, and managerial. Among the many challenges that could impact information sharing around responsible AI inside news organisations are knowledge silos, where information is isolated within one part of the organisation and not easily shared with others. This study aims to study how knowledge silos might affect the adoption of responsible AI practices in journalism through a cross-case study of four Dutch media outlets. We examine individual and organisational barriers to AI knowledge sharing and the extent to which knowledge silos could impede the operationalisation of responsible AI initiatives inside these newsrooms. To address this question, we conducted 14 semi-structured interviews with a strategic sample of editors, managers, and journalists at de Telegraaf, de Volkskrant, NOS, and RTL Nederland. The interviews aimed to uncover insights into the existence of knowledge silos, their effects on responsible AI practice adoption, and the organisational practices influencing these dynamics. Our results emphasise the importance of creating better structures for sharing information on AI across all layers of news organisations and highlight the need for research on knowledge silos as an impediment to responsible AI production.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Version of record, pdf, 755.4KB, Terms of use)
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- Publisher copy:
- 10.1080/1461670x.2025.2463589
Authors
- Publisher:
- Taylor & Francis
- Journal:
- Journalism Studies More from this journal
- Volume:
- 26
- Issue:
- 6
- Pages:
- 740-758
- Publication date:
- 2025-02-07
- Acceptance date:
- 2025-02-02
- DOI:
- EISSN:
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1469-9699
- ISSN:
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1461-670X
- Language:
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English
- Keywords:
- Pubs id:
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2086287
- Local pid:
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pubs:2086287
- Deposit date:
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2025-02-19
Terms of use
- Copyright holder:
- Dodds et al.
- Copyright date:
- 2025
- Rights statement:
- © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis GroupThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by theauthor(s) or with their consent.
- Licence:
- CC Attribution (CC BY)
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