AI检测怎么做？实测十款工具，这几个把老舍原作误判为AI

Core Viewpoint - The reliability of AI detection tools is under scrutiny due to significant discrepancies in their performance, leading to concerns about their application in academic and publishing contexts [2][9]. Group 1: AI Detection Tool Performance - A study evaluated 10 popular AI detection tools for text and image content, revealing inconsistent detection standards and high rates of false positives and negatives [2][3]. - Text detection tools showed a tendency to misclassify genuine articles as AI-generated, with nearly half of the tools failing to accurately identify AI content [3][4]. - The tool "茅茅虫" had the highest false positive rate, incorrectly identifying 99.9% of 老舍's "林海" as AI-generated, while others like 知网 and PaperPass performed accurately [4][5]. Group 2: Challenges in AI Detection - The detection of AI-generated content is complicated by the evolving nature of AI models and the potential for content to undergo modifications, which can obscure detection markers [9]. - Image detection tools performed well overall, but struggled with edited images, indicating a gap in recognizing modified content [8]. - Experts highlight that the current AI detection technology is still in an exploratory phase, necessitating ongoing development and a dual approach of technological advancement and regulatory frameworks [9][10].