首页|AIGC论文检测系统的技术缺陷与学术期刊因应

AIGC论文检测系统的技术缺陷与学术期刊因应

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探究AIGC论文检测系统的技术缺陷表征及其根源,从实操层面提出技术应对策略.文章利用知网AIGC检测服务系统和鉴字源AIGC文本识别系统,分别对10篇由ChatGPT生成的法学论文摘要及10篇由某款AI改写软件改写的法学论文摘要进行检测,以验证其AIGC鉴别能力.基于检测结果分析,可得出AIGC论文检测系统具有低准确度、高差异率、弱敏感性三大技术缺陷,而缺陷根源在于系统的模型训练不足、算法优化不当、预设词库匮乏.研究说明检测系统的完善依赖于系统研发与期刊发展的良性互动:在研发配合层面,学术期刊应当与技术提供商进行沟通合作,提供多样化的检测样本与预设词库;在行业发展层面,学术期刊应当以规避AI代写的学术不端行为和辩证利用AI生成的高质量与真实性知识内容作为最终目标;在编辑实践层面,期刊编辑应当发挥人机关系协同者的身份,引导系统的最优化发展.
Technical Defects of the AIGC Paper Detection System and Responses of Academic Journals
This paper explores the technical defects of the artificial intelligence-generated content (AIGC) paper detection system and its root causes and proposes the technical response strategies from the practical level. Using the AIGC detection service system of CNKI and the AI detector of "Jianziyuan",this research detects 10 legal paper abstracts generated by ChatGPT and 10 similar abstracts rewritten by an AI rewriting software to verify their AIGC identification abilities. Based on the analysis of the detection results,it can be concluded that the AIGC paper detection system has three major technical defects:the low accuracy,the high difference rate and the weak sensitivity. The root causes of the defects are insufficient model training,improper algorithm optimization,and lack of preset lexicons. The study shows that the improvement of the detection system depends on the benign interaction between system research and journal development:at the R&D coordination level,academic journals should communicate and cooperate with technology providers to provide diverse test samples and preset lexicons;at the industry development level,as the ultimate goal,academic journals should avoid the academic misconduct caused by AI ghostwriting and dialectically utilize the high-quality and authentic knowledge contents generated by AI;at the editorial practice level,journal editors should play the roles of human-computer relationship collaborators and guide the optimal development of the detection system.

AI-generated contentartificial intelligence generated content (AIGC)AI text detectionAIGC detection service system of CNKIAI director of "Jianziyuan"technical defectacademic journalresponse strategy

周濛

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深圳大学学报(人文社会科学版)编辑部

人工智能生成内容 AIGC AI文本检测 知网AIGC检测服务系统 鉴字源AIGC文本识别系统 技术缺陷 学术期刊 因应策略

2024

10.19619/j.issn.1007-1938.2024.00.027

出版与印刷
上海出版印刷高等专科学校

出版与印刷

影响因子：0.164
ISSN：1007-1938
年,卷(期)：2024.(4)