构建AI时代的科研诚信体系

Core Viewpoint - The emergence of artificial intelligence (AI) has led to new challenges in research integrity, including issues like "AI ghostwriting," "data embellishment," and "ghost authorship," which are critical for the healthy development of scientific endeavors [1][2]. Group 1: AI's Impact on Research Integrity - AI has significantly enhanced efficiency in knowledge acquisition, data analysis, and academic writing, but it has also fundamentally changed the composition of academic activities, leading to issues such as blurred contribution definitions, lack of transparency in research processes, and decreased interpretability of results [1][2]. - The rapid development of AI detection technologies has not kept pace with AI generation technologies, making traditional plagiarism detection methods less effective and allowing research misconduct to become more concealed and complex [1][2]. Group 2: New Challenges and Concerns - The application of generative AI has lowered the cost of academic fraud and increased the difficulty of detecting such actions due to the high quality of content generated by large language models [2]. - AI's involvement has blurred the boundaries of responsibility, raising questions about whether errors generated by AI should be considered "honest mistakes" or attributed to the user, and whether AI can be regarded as an author or co-author [2]. - There are concerns that AI-generated content could contaminate the human knowledge system, as evidenced by cases where fabricated "scientific news" has misled the public and undermined the credibility of knowledge [2]. Group 3: Recommendations for Addressing Challenges - A systematic and comprehensive approach is necessary to embrace technological innovation while firmly upholding research integrity, including deepening theoretical discussions and case studies to clarify AI's impact on research integrity [3]. - There is a need for comprehensive education on scientific ethics and AI skills training to guide researchers in the responsible use of AI tools [3]. - It is essential to build a governance system for scientific ethics that adapts to the AI era through global consensus and collaboration [3].