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ORIGINAL RESEARCH article
Front. Commun.
Sec. Media Governance and the Public Sphere
Volume 10 - 2025 | doi: 10.3389/fcomm.2025.1484186
This article is part of the Research Topic AI and Communication View all articles
Can AI-generated News Reduce Hostile Media Perceptions?
Provisionally accepted- Technical University of Kaiserslautern, Kaiserslautern, Germany
The current debate regarding artificial intelligence (AI) raises the question of whether AI-generated news articles on controversial topics can reduce news consumers' hostile media perceptions (HMP). In addition, there is a debate about people's prior attitudes towards AI and how it influences people's perceptions of AI-generated news articles. Based on the theoretical foundation of the MAIN model and the Hostile Media Phenomenon, we conducted two preregistered experimental studies in the United States (N = 1197). All subjects were presented with a news article on a divisive and polarizing topic (gun regulation), but we systematically varied the supposed author of the article (human journalist, AI-generated, AI and human journalist working together). In both studies exposure to the AI-generated news article significantly reduced participants' HMP. However, the effect was only detected for individuals with negative and moderate prior attitudes toward AI. Individuals with positive AI attitudes did not benefit from AIgenerated articles. AI-assisted news reporting showed very limited effects (only in Study 2). Furthermore, we examined if HMP predict online engagement. While Study 1 showed no effects on online engagement, Study 2 revealed that exposure to an AI-generated news article indirectly increased online engagement (intention to share a news article with friends and family). Implications for communication and journalism are discussed.
Keywords: AI-generated news, AI attitudes, hostile media perceptions, online engagement, experiment
Received: 21 Aug 2024; Accepted: 14 Feb 2025.
Copyright: © 2025 Huh, Kubin and von Sikorski. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Christian von Sikorski, Technical University of Kaiserslautern, Kaiserslautern, Germany
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