The Effects of AI Automated Journalism in the Perspective of Intelligent Communication

Abstract

This study explores the multifaceted impacts of AI-driven automated news production on industry transformation, gatekeeping mechanisms, and audience cognition within the framework of intelligent communication. Through in-depth interviews and case analysis, combined with surveys of news practitioners, social media bloggers, and frequent news consumers aged 18-45, the study finds that AI technology, through data scraping, algorithmic recommendations, and automated editing, has significantly improved news production efficiency and reduced labor costs. However, it also leads to skill hollowing-out among practitioners and increased ethical risks. The dual-track gatekeeping mechanism of algorithms and human collaboration enhances content safety but faces tensions between standardization and innovation, as well as between technological rationality and humanistic values. For audiences, AI news reshapes information reception pathways through targeted recommendations, but it also triggers a “human-machine trust paradox,” where rational skepticism coexists with emotional dependence, and the logic of traffic exacerbates the echo chamber effect. The study proposes the need to build a “technology-ethics” collaborative governance framework to balance efficiency and professional values, providing theoretical insights and practical references for the transformation of the news industry in the era of intelligent communication.