Analysis of Pathways for Preventing and Mitigating Risks in Generative AI Communication

The rapid development of generative artificial intelligence (AI) technology is profoundly reshaping the underlying logic of information production and distribution[9]. However, while enhancing creative efficiency, it also induces global communication risks such as information distortion, value infiltration, copyright disputes, and the erosion of social trust. This paper, from a communication studies perspective, combines framing theory and algorithmic governance logic to analyze the risk generation mechanism intertwined with training dataset bias, the "black box" nature of models, and social network algorithmic distribution. Through comparative research on cutting-edge international governance cases (such as the EU's AI Act) and local Chinese practices, this paper proposes to construct a comprehensive governance framework that is interdisciplinary and multi-dimensional. Research shows that the key to preventing and mitigating risks lies in: establishing a closed-loop algorithmic responsibility system covering the entire process of technology development, content distribution, and user feedback; improving digital watermarking and traceability technology standards for generative content; and deepening international soft law coordination through platforms such as UNESCO. Furthermore, systematically improving public media literacy is the social foundation for preventing the spread of misinformation. The research conclusions of this paper aim to provide theoretical support and practical guidance for building a safe, controllable, and multi-governance communication ecosystem[11].