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Can you fool AI by doing a 180? - A case study on authorship analysis of texts by Arata Osada

机译:你可以通过做180岁欺骗AI吗? - Arata Osada文本作者分析的案例研究

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This paper is our attempt at answering a twofold question covering the areas of ethics and authorship analysis solutions. 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 several works of Arata Osada, a Japanese educator and specialist in the history of education, with half of them being books written before the Second World War and another half in the 1950s, in between which the author 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 by Arata Osada 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.
机译:本文是我们在回答涵盖道德和作者分析解决方案领域的双重问题的尝试。首先,由于用于执行作者分析的方法意味着作者可以通过他或她创建的内容来识别,因此我们有兴趣了解作者识别系统是否有可能正确地将其工作到作者(如果在他们经历了一个主要的心理转变。其次 - 从作者道德价值观的演变的角度来看 - 我们检查了作者归因系统是否遇到检测单个作者的困难,这将是意味着什么。我们首先使用基于预先训练的变压器模型的文本分类器执行二进制作者分析任务来回答这些问题,以及依赖于传统相似度量的基线方法。对于测试集,我们选择了arata Osada,日本教育家和教育历史专家的几个作品,其中一半是在第二次世界大战之前写的书籍,在20世纪50年代的另一半在哪个作者接受了在政治意见方面转变。因此,我们能够确认在Arata Osada在超过10年的时间范围内的文本的情况下,虽然分类精度下降大幅下降,并且基本上低于其他非虚构的文本作家,预测的置信度分数保持在类似的水平,如较短的时间跨度的情况,表明分类器在许多情况下欺骗决定arata oSada在多年的时间范围内的时间跨越了arata osada的文本两个不同的人,这反过来导致我们相信这种变化会影响作者分析,并且历史事件对一个人的伦理前景产生了很大影响,正如他们的着作中所表达的那样。

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