Group 1 - The core viewpoint of the articles highlights the various deceptive practices in online shopping platforms, including hidden fees and price manipulation, which undermine consumer trust and regulatory effectiveness [1][2][3] Group 2 - The first article discusses the issue of hidden fees in online ticket purchasing, where consumers often end up paying more than expected due to additional charges that are not clearly disclosed [1] - The second article addresses the unauthorized price adjustments made by platforms, which disrupt the pricing autonomy of merchants and negatively impact both merchants and consumers [2] - The third article focuses on the misuse of AI models in e-commerce, where businesses create misleading representations of products, leading to consumer dissatisfaction and potential legal repercussions [3]

Core Viewpoint - The article discusses the misuse of AI-generated images in the e-commerce sector, particularly in the context of "only refund" requests, highlighting the challenges faced by merchants due to the increasing sophistication of these fraudulent practices [3][6]. Group 1: AI Image Fraud in E-commerce - AI-generated fake images have become prevalent, particularly in the categories of clothing, food, and daily necessities, leading to a surge in "only refund" requests [7][8]. - Merchants report that the realism of AI-generated images complicates the refund verification process, making it difficult to distinguish between genuine and fraudulent claims [28][29]. - The phenomenon has sparked polarized discussions among consumers, with some mocking the intelligence of those attempting to exploit the system, while others express concern over the erosion of trust in e-commerce [29][30]. Group 2: Experimentation with AI Refund Claims - The article details an experiment conducted by the author to test the effectiveness of AI in generating images for refund claims, revealing that the technology is already well-integrated into the refund process across major platforms [31][32]. - The experiment involved selecting products that are easy to manipulate visually, such as transparent items and perishable goods, to exploit the weaknesses in platform verification systems [32][33]. - The results showed that refund requests were processed quickly and without thorough scrutiny, indicating significant loopholes in the current e-commerce refund policies [41][51]. Group 3: Governance and Solutions - The article suggests that addressing the issue of AI-generated refund fraud requires a multi-faceted approach involving legal, technological, and regulatory measures [57][58]. - Legal frameworks exist to penalize fraudulent refund claims, with potential civil and criminal liabilities for consumers who exploit these systems [59][61]. - Recommendations for platforms include establishing consumer trust rating systems, enhancing image verification technologies, and improving refund request auditing processes to mitigate fraudulent activities [64][66].