Group 1 - The article emphasizes the potential of the AI identification system in addressing the challenges of misinformation, highlighting its role as a crucial front-end support in content governance [1][4] - It points out that over 20% of the 50 high-risk AI-related public opinion cases in 2024 were related to AI-generated rumors, indicating a significant issue in the current content landscape [1][3] - The article discusses the three main challenges posed by AI-generated harmful content: lower barriers to entry, the ability for mass production of false information, and the increased realism of such content [3][4] Group 2 - The introduction of a dual identification mechanism, consisting of explicit and implicit identifiers, aims to enhance the governance of AI-generated content by covering all stakeholders in the content creation and dissemination chain [5][6] - The article notes that explicit identifiers can reduce the credibility of AI-generated content, as studies show that labeled content is perceived as less accurate by audiences [6][8] - It highlights the limitations of the AI identification system, including the ease of evasion, forgery, and misjudgment, which can undermine its effectiveness [8][9] Group 3 - The article suggests that the AI identification system should be integrated into the existing content governance framework to maximize its effectiveness, focusing on preventing confusion and misinformation [11][12] - It emphasizes the need to target high-risk areas, such as rumors and false advertising, rather than attempting to cover all AI-generated content indiscriminately [13][14] - The responsibilities of content generation and dissemination platforms should be clearly defined, considering the challenges they face in accurately identifying AI-generated content [14]