“This is how journalism has always been done”: White neutrality, newsroom norms, and an AI intervention in source diversification

This study draws on interviews with 12 journalists in a Canadian newsroom to examine how they understand source diversification, how they perceive AI-based source-tracking technology, and how their reflections illuminate discourse on race and accountability in journalism. Based on semi-structured interviews conducted after a demonstration of the technology, the analysis identifies the motivations and barriers shaping source diversification, including professional norms, representational goals, time constraints, and institutional culture. Reporters express commitments to inclusive sourcing, but remain constrained by routines that privilege official voices, anticipated by research analysis like framing and indexing theories. Participants describe the AI tool, which quantitatively scores sources according to their relationship to societal power structures, as a potential catalyst for reflective practice and accountability. They also suggest the technology may sit uneasily within professional norms. The study is contextualized in research about role performance and race in newsrooms. Finally, this AI-based source-tracking technology resituates journalism within a Bourdieusian field, pulled toward social and cultural capital in relation to structural racism.

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Publication Details

Journal
Journalism
Published
2026-08-27
DOI
https://doi.org/10.1177/14648849261484320
Primary Topic
Media Studies and Communication
Type
article
Field-Weighted Citation Impact
0.00
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article

“This is how journalism has always been done”: White neutrality, newsroom norms, and an AI intervention in source diversification

Asmaa Malik, Gavin Adamson, Shari Okeke, Jisele Bayley-Hay
Journalism
Media Studies and Communication
article

“This is how journalism has always been done”: White neutrality, newsroom norms, and an AI intervention in source diversification

Asmaa Malik, Gavin Adamson, Shari Okeke, Jisele Bayley-Hay
article en

Abstract

This study draws on interviews with 12 journalists in a Canadian newsroom to examine how they understand source diversification, how they perceive AI-based source-tracking technology, and how their reflections illuminate discourse on race and accountability in journalism. Based on semi-structured interviews conducted after a demonstration of the technology, the analysis identifies the motivations and barriers shaping source diversification, including professional norms, representational goals, time constraints, and institutional culture. Reporters express commitments to inclusive sourcing, but remain constrained by routines that privilege official voices, anticipated by research analysis like framing and indexing theories. Participants describe the AI tool, which quantitatively scores sources according to their relationship to societal power structures, as a potential catalyst for reflective practice and accountability. They also suggest the technology may sit uneasily within professional norms. The study is contextualized in research about role performance and race in newsrooms. Finally, this AI-based source-tracking technology resituates journalism within a Bourdieusian field, pulled toward social and cultural capital in relation to structural racism.

Journalism
Toronto Metropolitan University (CA)
Reduced inequalities
Openalex Percentile: Top 5%
Media Studies and Communication
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