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换脸换声、版权侵权 生成式AI使用如何筑牢“防火墙”?
Yang Shi Wang·2025-10-21 22:42

Core Insights - The report from the China Internet Network Information Center indicates that the user base for generative artificial intelligence products in China has reached 515 million people, highlighting the rapid proliferation of this technology [1] - The report also emphasizes the emerging issues related to generative AI, such as deepfake technology leading to false advertising, copyright infringement, and academic misconduct [1] Group 1: Deepfake Technology and Its Implications - The multi-modal capabilities of generative AI allow users to easily swap faces and voices in videos, leading to an increase in fraudulent activities, including the creation of fake advertisements [1] - Recent cases include the impersonation of Olympic champions and doctors to mislead the public, showcasing the potential for misuse of this technology [1] - Experts suggest that the best way to identify deepfake content is through AI-based detection methods that analyze unnatural features in videos and audio [2][4] Group 2: Governance and Regulation - Experts advocate for the implementation of a comprehensive content labeling system to manage the proliferation of deepfake technology [5] - Starting from September 2025, a new regulation will require all AI-generated content to include explicit labels, encouraging the use of digital watermarks to ensure traceability [5] - The distinction between legal and illegal applications of AI face-swapping technology is crucial, with legitimate uses including film production and education, while illegal uses involve unauthorized impersonation and misinformation [7] Group 3: Copyright Issues in AI Training - The training of AI models often involves data sourced from the internet, which may include copyrighted material, leading to significant copyright disputes [8][9] - Experts emphasize the need for AI developers to establish compliance mechanisms for copyright, including obtaining permissions and maintaining records of data sources [11] - Regulatory bodies are encouraged to expand data supply channels to address the conflict between insufficient training data and copyright concerns [12] Group 4: Academic Integrity Challenges - The use of generative AI by students and researchers for writing papers and completing assignments poses a challenge to academic integrity [13] - Experts suggest that instead of outright bans, a more effective approach is to guide students in the proper use of AI tools to enhance learning and research efficiency [13] - Educators are encouraged to design assessments that evaluate students' thought processes rather than relying solely on text submissions, thereby reducing the temptation to misuse AI [13]