Core Viewpoint - The rise of AI-generated images in food delivery services has led to significant consumer dissatisfaction and trust issues, as many businesses use misleading visuals to attract customers [1][2][3]. Group 1: AI-Generated Images and Consumer Impact - Many food delivery platforms are using AI-generated images that do not accurately represent the actual products, leading to a disconnect between consumer expectations and reality [1][2]. - Some businesses are misrepresenting themselves as having dine-in options by using AI-generated images, which can create a false sense of security regarding hygiene and dining conditions [2][3]. Group 2: Regulatory and Platform Responsibilities - The use of AI-generated images raises concerns about false advertising, but the lack of severe consequences for individual consumers may limit regulatory intervention [3]. - Platforms have a responsibility to monitor the qualifications and hygiene conditions of the merchants they host, but conflicts of interest may hinder strict oversight [3][4]. - Recent investigations revealed that some food delivery merchants have been using forged food business licenses, indicating a broader issue of compliance within the industry [4]. Group 3: Industry Implications - The emergence of a new industry around AI-generated promotional materials for food delivery services highlights the need for clearer regulations and accountability [4]. - The ongoing issues in the food delivery sector, including the use of misleading advertising and compliance violations, necessitate urgent attention from both platforms and regulatory bodies [4].

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]