Content over appearance: What drives Indonesian youth's trust in AI news presenters

This study examined the Indonesian youth's perceptions of the trustworthiness of artificial intelligence (AI) news presenters. The theoretical framework employed is cognitive psychology and journalistic ethics, and data were obtained via a questionnaire from 120 high school students. Instead of traditional statistical analysis, this study utilized a proposed interpretable machine learning frameworks that benefit from offering more detailed analysis on perception prediction and AI news presenters parameter setting for specific expected performance. The findings demonstrate that Indonesian youth's impression of credibility toward AI news presenters is driven by content credibility rather than the credibility of the medium showcasing the AI news presenter. Content clarity is the most significant factor influencing this perception, while human-like appearance is the least influential factor in Indonesian youth's perceptions of AI news presenters. Also, it details specific contributing factors for certain expected performance, particularly AI news presenters, in the context of the Global South.

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Publication Details

Journal
Media International Australia
Published
2026-03-28
DOI
https://doi.org/10.1177/1329878x261435003
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Content over appearance: What drives Indonesian youth's trust in AI news presenters

Indra Prawira, Ebnu Yufriadi, Nur Afny Catur Andryani, Muhammad Rizqullah Ramadhan
Media International Australia
Computational and Text Analysis Methods
article

Content over appearance: What drives Indonesian youth's trust in AI news presenters

Indra Prawira, Ebnu Yufriadi, Nur Afny Catur Andryani, Muhammad Rizqullah Ramadhan
article en

Abstract

This study examined the Indonesian youth's perceptions of the trustworthiness of artificial intelligence (AI) news presenters. The theoretical framework employed is cognitive psychology and journalistic ethics, and data were obtained via a questionnaire from 120 high school students. Instead of traditional statistical analysis, this study utilized a proposed interpretable machine learning frameworks that benefit from offering more detailed analysis on perception prediction and AI news presenters parameter setting for specific expected performance. The findings demonstrate that Indonesian youth's impression of credibility toward AI news presenters is driven by content credibility rather than the credibility of the medium showcasing the AI news presenter. Content clarity is the most significant factor influencing this perception, while human-like appearance is the least influential factor in Indonesian youth's perceptions of AI news presenters. Also, it details specific contributing factors for certain expected performance, particularly AI news presenters, in the context of the Global South.

Media International Australia
Binus University (ID)
Openalex Percentile: Top 13%
Computational and Text Analysis Methods
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