Core Viewpoint - The increasing reliance on AI detection systems for academic integrity is leading to significant misjudgments, causing concern among students regarding the originality of their work [1][2][3] Group 1: AI Detection Issues - Many students report high AI detection rates in their theses, with some reaching as high as 90%, raising fears of misjudgment [1] - Classic literary works have also been flagged by AI detection systems, with instances of 100% AI generation likelihood, indicating a flaw in the technology [1] - The current AI detection methods, based on machine learning and natural language processing, have limitations that lead to frequent misjudgments [2] Group 2: Limitations of AI Detection Technology - The variability of language makes it difficult for AI systems to accurately determine the source of text, resulting in misjudgments [2] - As generative AI improves, its outputs increasingly resemble human writing, complicating the detection process [2] - Inadequate training data and simplified detection processes for efficiency can further reduce the accuracy of AI detection systems [2] Group 3: Recommendations for Improvement - There is an urgent need to enhance the accuracy and credibility of AI detection technologies through improved standards and regulations [3] - Establishing a standardized system that covers technical principles, data application, and result evaluation is essential for reliable detection [3] - Implementing regular audits by third-party organizations can ensure the transparency and accuracy of detection algorithms, preventing conflicts of interest [3]