With the deep integration of generative artificial intelligence (AI, such as ChatGPT, DeepSeek) into the entire publishing workflow, the industry has achieved intelligent innovation in content creation, editing and proofreading, and dissemination. However, this transformation also introduces a series of emerging cultural security risks. These risks not only challenge the traditional functions of publishing in ideological guidance, cultural value inheritance, and social consensus building, but also pose potential threats to national cultural security. Currently, the principle of "shifting checkpoints forward and prioritizing prevention" has become a consensus in cultural risk governance, necessitating the establishment of a more forward-looking and systematic risk prevention and control system. This paper introduces the concept of feedforward control, exploring how to predict, pre-screen, warn, and pre-control risks before they materialize, thereby providing theoretical insights and practical pathways for the publishing industry to safeguard security boundaries and achieve high-quality development during its intelligent transformation.

The research proceeds in three stages. First, through case analysis, it examines the specific practices of artificial intelligence technology in reshaping the entire "creation—editing—dissemination" workflow and driving the intelligent transformation of the publishing industry. Second, it identifies potential risks such as value-orientation bias, copyright infringement concerns, and social cognitive disparities. Third, guided by the concept of feedforward control, the research designs specific mechanisms for risk prediction, pre-screening, early warning, and pre-control throughout the four key publishing stages—topic planning, creation, review, and distribution. This forms a human-machine collaborative, end-to-end risk prevention and control system that enhances the cultural security resilience and risk response capacity of the publishing industry in its intelligent transformation.

The findings reveal that while artificial intelligence significantly enhances publishing efficiency and user experience, it also gives rise to three prominent categories of cultural security risks. First, algorithmic bias and data inclination in machine-generated content may dilute mainstream ideologies. Second, in the "human-machine collaboration" models, the transfer of editorial gatekeeping authority complicates the identification and traceability of copyright infringements. Third, algorithm-driven recommendation and AI-assisted reading intensify the "information cacoon" effect, weakening publishing's role in fostering social consensus. Examining the risks of AI-empowered publishing is not only a practical necessity for safeguarding China's cultural security but also a critical issue concerning the civilizational security in human knowledge production and dissemination.

To address these risks, this paper proposes constructing a feedforward-controlled risk prevention system spanning the entire publishing workflow. Specific measures include: predicting cultural value-orientation risks in topic planning; pre-screening compliance and copyright infringement risks in content creation; establishing human-machine collaborative early warning mechanisms in the review stage; and utilizing algorithm simulation technology to pre-control dissemination risks in distribution. The system emphasizes upstream risk governance by implementing multi-tiered safeguards and human-machine collaboration, achieving multi-level risk interception from the source to the terminal. It not only helps the publishing industry safeguard cultural security and fulfill its cultural mission amid the intelligentization trend, but also provides practical reference for national cultural governance in the context of AI-cultural industry integration, ultimately contributing to the high-quality development of publishing and the building of a culturally strong nation.