Knowledge Silos as a Barrier to Responsible AI Practices in Journalism? Exploratory Evidence from Four Dutch News Organisations

Abstract

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.

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