Core Viewpoint - The integration of artificial intelligence (AI) in academic publishing presents both opportunities for efficiency and risks related to academic integrity and innovation [1][2][3] Group 1: AI's Role in Academic Publishing - AI technology, particularly generative AI, is significantly enhancing the efficiency of academic publishing, with over 90% of document processing tasks at CNKI being completed by machines [1] - The rapid development of AI models is deeply embedding itself in the writing and publishing of scientific journals, which raises concerns about potential risks, such as data leaks during the peer review process [1] Group 2: Challenges and Risks - Over-reliance on AI may challenge academic innovation, as it primarily depends on historical data and may introduce algorithmic biases, potentially harming research originality and raising issues of academic integrity [2] - There is currently no consensus in the industry regarding the boundaries of generative AI's application in academic publishing, highlighting the need for clear regulations [2] Group 3: Regulatory Measures and Tools - The implementation of specific rules for AI usage in academic publishing requires effective technical supervision, with CNKI actively exploring academic achievement detection and developing a generative AI detection tool for educational institutions [3] - Existing guidelines, such as the "Guidelines for the Use of AIGC in Academic Publishing 2.0," have been established, but further refinement is needed to clarify the scenarios and extent of AI usage [2]