论文标题
您可以通过180欺骗AI吗? $ \ unicode {x2013} $关于Arata Osada的作者资格分析的案例研究
Can You Fool AI by Doing a 180? $\unicode{x2013}$ A Case Study on Authorship Analysis of Texts by Arata Osada
论文作者
论文摘要
本文是我们尝试回答一个涵盖道德和著作分析领域的双重问题的尝试。首先,由于用于执行作者身份分析的方法意味着他或她创建的内容可以认可作者,因此我们有兴趣找出作者身份证系统是否可以正确地将作品归因于作者,如果他们在多年来经历了主要的心理过渡。其次,从作者道德价值观的演变的角度来看,我们检查了如果作者归因系统在检测单个作者身份方面遇到困难,这将是什么意思。我们着手使用基于预训练的变压器模型的文本分类器执行二进制作者资格分析任务来回答这些问题,并依靠常规相似性指标来回答这些问题。在测试套装中,我们选择了教育史上的日本教育者和专家阿拉塔·奥萨达(Arata Osada)的作品,其中一半是在第二次世界大战之前写的书,在1950年代又写了一半,在这两者之间,他对政治观点进行了转变。结果,我们能够确认,如果在十多年的时间范围内由阿拉塔·奥萨达(Arata Osada)撰写的文本,而分类准确性下降了很大的差距,并且大大低于其他非小说作家的文本,那么预测的信心得分仍然是在较短的时间范围的情况下,这些预测的时间范围是较短的时间,这表明较短的范围是在较短的时间范围内的范围。实际上是由两个不同的人撰写的,这反过来又使我们相信这种变化会影响作者身份分析,并且历史事件对人的著作中表达的道德观念产生了很大的影响。
This paper is our attempt at answering a twofold question covering the areas of ethics and authorship analysis. Firstly, since the methods used for performing authorship analysis imply that an author can be recognized by the content he or she creates, we were interested in finding out whether it would be possible for an author identification system to correctly attribute works to authors if in the course of years they have undergone a major psychological transition. Secondly, and from the point of view of the evolution of an author's ethical values, we checked what it would mean if the authorship attribution system encounters difficulties in detecting single authorship. We set out to answer those questions through performing a binary authorship analysis task using a text classifier based on a pre-trained transformer model and a baseline method relying on conventional similarity metrics. For the test set, we chose works of Arata Osada, a Japanese educator and specialist in the history of education, with half of them being books written before the World War II and another half in the 1950s, in between which he underwent a transformation in terms of political opinions. As a result, we were able to confirm that in the case of texts authored by Arata Osada in a time span of more than 10 years, while the classification accuracy drops by a large margin and is substantially lower than for texts by other non-fiction writers, confidence scores of the predictions remain at a similar level as in the case of a shorter time span, indicating that the classifier was in many instances tricked into deciding that texts written over a time span of multiple years were actually written by two different people, which in turn leads us to believe that such a change can affect authorship analysis, and that historical events have great impact on a person's ethical outlook as expressed in their writings.