Dancing with AI: The Impact of AI-Generated Images and Videos on Chinese Visual Journalism
Jing Meng, Haiyan Wang · Digital Journalism · 2025
The increasing use of AI for automating visual representation raises concerns about issues such as deepfakes and challenges the long-standing belief of photography as a powerful tool for witnessing and documenting. This study explores the use of AI-generated images and videos by Chinese visual journalists, examining how they are reshaping visual journalism by transforming journalistic claims of visual truth, work routines, and journalistic autonomy, particularly in relation to human–machine agency. We argue that journalists’ conceptions of visual truth reflect different understandings of “mechanical objectivity,” combining both objective recording and subjective rendering. The growing emphasis on the human and subjective aspects of news production serves as a discursive strategy to navigate AI-related anxieties, the rise of machine agency, and the decline in work meaningfulness. These shifts also reveal the power dynamics of AI-driven news production both within and outside the newsroom, as a top-down AI strategy is closely tied to government support and external platform companies. This article contributes to the current scholarship on AI and journalism by showing how journalistic agency is disrupted and negotiated through perceptions, routines, and power struggles in an increasingly automated news industry.