电商上演「魔法对轰」：卖家用AI假图骗下单，买家拿AI烂水果骗退款

Core Viewpoint - The article discusses the increasing misuse of AI technology by both buyers and sellers in e-commerce, leading to a trust crisis and the need for better verification methods to combat fraud [2][10][21]. Group 1: Buyer Misuse of AI - Some buyers are using AI-generated images to falsely claim product defects in order to obtain refunds, exploiting the difficulty of verifying the condition of perishable goods like fruits [2][6]. - This practice has evolved from earlier methods where buyers used basic photo editing tools, making it harder for sellers to detect fraud due to the sophistication of AI-generated images [8][10]. - The phenomenon reflects a "tit-for-tat" mentality among buyers who have previously been deceived by sellers using AI-enhanced product images [10][21]. Group 2: Seller Misuse of AI - Sellers are also misusing AI to create misleading product images, over-enhancing ordinary items, and generating fake reviews, which contributes to the issue of "goods not matching the description" [10][24]. - The article highlights that sellers may use virtual models and AI-generated content to cut costs, further complicating the authenticity of product representations [10][24]. Group 3: Proposed Solutions - Various proposed solutions to combat this issue include requiring buyers to submit videos of defective products, taking multiple photos from different angles, and using in-app cameras to prevent the upload of AI-generated images [11][15][24]. - However, these solutions have limitations, as advanced AI tools can still generate convincing content, making it challenging to establish foolproof verification methods [11][15][23]. Group 4: Technological Innovations - The article suggests that implementing digital watermarking and content provenance technologies could help in identifying and tracing AI-generated content, thus enhancing trust in e-commerce [19][21]. - The development of standards like C2PA and tools such as Google's SynthID aims to embed invisible watermarks in AI-generated media, which could serve as a digital identity for content [19][21][26]. Group 5: Ongoing Challenges - The ongoing "cat-and-mouse" game between AI generation and detection technologies poses a continuous challenge, as both sides evolve rapidly [23][24]. - E-commerce platforms are exploring various strategies, including strengthening evidence chains and utilizing big data analytics to monitor user behavior and detect anomalies [24][26].