10个视频9个看走眼：连真视频都打Sora水印碰瓷，这世界还能信啥？

Core Viewpoint - The article discusses the challenges posed by AI-generated content, particularly videos, and the need for effective detection methods to prevent misinformation and maintain social trust [7][9][30]. Group 1: AI-Generated Content Challenges - AI-generated videos are becoming increasingly difficult to distinguish from real videos, leading to widespread confusion and skepticism among internet users [2][5]. - The rapid advancement of AI technology necessitates mandatory watermarking of AI-generated content to mitigate the risk of misinformation [7][9]. - A recent incident highlighted the ease with which real videos can be manipulated to appear as AI-generated by adding watermarks, complicating the detection process [11][13]. Group 2: Detection Tools and Their Effectiveness - Several tools have been developed to detect AI-generated content, each with varying degrees of accuracy: - AI or Not: Claims an accuracy rate of 98.9% for detecting AI-generated content across various media types [17]. - CatchMe: Offers video detection capabilities but has shown low accuracy in tests [20][21]. - Deepware Scanner: Focuses on deepfake detection but often fails to scan videos [24][25]. - Google SynthID Detector: Specifically identifies content generated or edited by Google AI models [28][29]. - Overall, the effectiveness of these detection tools is inconsistent, indicating that the development of reliable AI detection technology is still a work in progress [30].