Core Viewpoint - A new trend of "sheep shearing" using AI-generated fake images for refund requests is emerging in the e-commerce sector, posing challenges for merchants in identifying and managing these fraudulent activities [1][2][5]. Group 1: AI-Generated Fake Images - Merchants report that some buyers are using AI tools to create fake images to apply for refunds, making it difficult for businesses to verify the authenticity of claims [1][2]. - The identification of AI-generated fake images relies heavily on manual inspection, and even when anomalies are detected, proving the buyer's dishonesty remains challenging [1][3]. - The frequency of encountering AI-generated fake images is not high, but it still occurs monthly for many merchants [2][3]. Group 2: Refund Policy Challenges - The current refund policy allows for automatic processing of refund requests, with only 1% to 3% requiring manual review, complicating the detection of fraudulent claims [3][4]. - Merchants often face difficulties in handling suspicious refund requests, as customers may refuse to cooperate during the return process [3][4]. - The implementation of refund policies has led to an increase in contentious refund requests, prompting platforms to encourage negotiation between merchants and buyers [4][5]. Group 3: Legal and Ethical Implications - The use of AI-generated fake images to claim refunds may violate legal principles of honesty and could be classified as civil fraud [5][6]. - Legal experts suggest that sellers have the right to challenge fraudulent refund claims in court, and if the fraudulent behavior is significant, it could lead to criminal charges [5][6]. - E-commerce platforms are encouraged to support sellers in appealing against fraudulent claims and to improve their verification processes [6][9]. Group 4: Industry Collaboration and Solutions - There is a call for collaborative efforts within the industry to create a healthier ecosystem to combat the misuse of AI technology [7][12]. - AI service providers are urged to implement watermarking and other identification measures to prevent the misuse of generated content [9][10]. - The introduction of regulations requiring AI-generated content to have clear identification marks is seen as a necessary step to mitigate risks associated with fraudulent activities [10][11].

Core Viewpoint - The article discusses the increasing issue of fraudulent refund claims in e-commerce due to the misuse of AI technology, highlighting a case where a customer used AI-generated content to deceive a seller into issuing a refund. This situation reflects a broader trend where both consumers and sellers are caught in a cycle of deception facilitated by AI tools. Group 1: Fraudulent Activities - A case in Jiangsu involved a seller who faced a refund request for "6 dead crabs," which was later revealed to be a scam using AI-generated videos [6][10] - The rise of AI image editing has made it easier for consumers to create convincing fake evidence to support refund claims, leading to significant challenges for sellers [7][12] - The cost of creating fake images has become nearly zero, allowing consumers to exploit refund policies with minimal effort [12][14] Group 2: Seller Challenges - Many sellers report that even obvious fake images are often accepted by e-commerce platforms, leading to financial losses [8][16] - The rapid approval of refund requests, sometimes within minutes, has left sellers vulnerable to fraudulent claims [10][16] - Sellers are forming mutual aid groups to share experiences and strategies for identifying fake claims and protecting their businesses [25][26] Group 3: Consumer Experience - Consumers are also facing challenges as AI-generated images can misrepresent products, leading to dissatisfaction upon receiving items that do not match their expectations [18][20] - The use of AI digital models in marketing has created confusion among consumers regarding the actual quality of products [18][23] Group 4: Regulatory Response - A commitment has been made by major e-commerce platforms to establish guidelines for the ethical use of AI technology, aiming to address the issues of fraud and misrepresentation [24][26] - Despite existing regulations, enforcement remains a challenge, and sellers often find themselves needing to fight for their rights [25][26] - E-commerce platforms are beginning to develop AI detection capabilities to combat fraudulent activities, but these measures are still in the early stages [26]

Group 1 - The core issue revolves around consumers being required to destroy products to receive refunds, highlighting a significant trust crisis in the online shopping environment [2][3] - The "only refund" policy, initially intended to eliminate low-quality products, has been misused by some consumers, leading to a detrimental impact on merchants [3][4] - Major platforms have begun to cancel or optimize the "only refund" policy since April, but it still exists in a modified form where merchants and consumers negotiate [3][4] Group 2 - The platforms hold the responsibility to create more refined rules and services regarding the "only refund" policy, rather than evading accountability [4] - Legal frameworks dictate that merchants cannot require product destruction as a condition for refunds, indicating a need for better enforcement of consumer rights [4] - The initial intent of the "only refund" policy was positive, but execution has faltered, necessitating ongoing improvements in service and rule alignment by platforms [4]

Group 1 - The controversial "refund only" policy has been completely phased out by major e-commerce platforms in April, with platforms like Taobao, Pinduoduo, JD.com, Douyin, and Kuaishou updating their after-sales rules to prioritize merchants in handling refund requests [1][3] - Taobao was the first to implement the "refund only" model in 2021, which initially boosted GMV but ultimately led to significant losses for many sellers, contributing to a wave of store closures that continues into 2025 [3][4] - The closure of numerous Taobao stores, including those of prominent influencers, reflects a broader trend of declining profitability and increasing operational challenges faced by e-commerce sellers [4][7][10] Group 2 - The rising return rates in the clothing industry have severely impacted seller confidence, with some sellers reporting return rates soaring from 30% to as high as 80% after the introduction of new policies [11][13] - High advertising costs and an increasingly competitive promotional environment have further strained the profitability of many sellers, leading to a situation where they are "losing money to gain visibility" [14][15] - Despite the challenges, some sellers are finding success through innovative models such as content e-commerce and cross-border e-commerce, with examples of brands achieving significant sales growth on platforms like Douyin and TikTok [15][20][21]