The Metajournalistic Discourse and the Sociopolitical Construction of AI Risk in Chinese Journalism

Youyi Wei
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Youyi Wei: School of Journalism and Communication, The Chinese University of Hong Kong, China

Media and Communication, 2026, vol. 14

Abstract: The integration of artificial intelligence (AI) into journalism has improved production efficiency but raised concerns about its potential to compromise content quality and undermine journalists’ professional capacity. These tensions are particularly pronounced in China, where AI deployment in journalism intersects with state-led advocacy and professional authority. Drawing on metajournalistic discourse and taking a sociopolitical perspective, I examine how journalistic discourse frames and responds to AI risks in structurally constrained contexts. I conducted a textual analysis of 102 articles published between 2022 and 2025 by Chinese journalists affiliated with institutional media. These articles narrate journalists’ perceptions of, or working experiences with, AI. AI risks are discursively framed at three levels: content quality, mainstream values, and professional subjectivity. Journalistic discourse constructs an asymmetrical attribution of these risks, assigning responsibility primarily to opaque AI systems, technology companies, and individual journalists positioned as “risk filters,” while largely overlooking the responsibilities of media organizations and the state. Political intervention, institutional hierarchy, and professional commitments shape adaptive boundary work that aligns with state-led AI advocacy while establishing boundaries by limiting AI capability in journalistic work. This study provides an empirical account of how journalists negotiate AI risks and professional autonomy amid advanced AI development and state-sanctioned boundaries, extending Western-centric and Global South research.

Keywords: AI; AI risks; Chinese journalism; journalism; metajournalistic discourse; sociopolitical context (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:cog:meanco:v14:y:2026:a:12413

DOI: 10.17645/mac.12413

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