Core Viewpoint - The Internet Engineering Task Force (IETF) has proposed the "AI Content Disclosure Header" draft to address the challenge of distinguishing between AI-generated and human-generated content on the internet, aiming to mitigate the spread of false information generated by AI systems [1][3][11]. Group 1: IETF's Proposal - The IETF's draft aims to introduce machine-readable AI content markers in HTTP responses to indicate the nature of AI involvement in content generation [2][13]. - The proposed markers include details such as the AI model used, the organization providing the AI system, the reviewing entity, and the generation timestamp [2][13]. Group 2: Challenges in AI Content - A significant issue in the AI field is the circular referencing of false content by different AI products, leading to the phenomenon of "making falsehoods true" and disrupting the internet content ecosystem [3][11]. - AI hallucinations, where AI generates plausible but incorrect information, pose a challenge, as AI models rely on probabilistic predictions rather than factual accuracy [6][11]. Group 3: Implications of AI Content - The interdependence of AI systems can create a closed loop of misinformation, where false content is perpetuated across different platforms, ultimately affecting users [9][11]. - The IETF's initiative seeks to prevent the recycling of AI-generated false content into the internet, thereby avoiding a negative feedback loop of "garbage in, garbage out" in AI training data [11][13].