The emergence of large language models (LLMs) capable of generating realistic
texts and images has sparked ethical concerns across various sectors. In
response, researchers in academia and industry are actively exploring methods
to distinguish AI-generated content from human-authored material. However, a
crucial question remains: What are the unique characteristics of AI-generated
text? Addressing this gap, this study proposes StyloAI, a data-driven model
that uses 31 stylometric features to identify AI-generated texts by applying a
Random Forest classifier on two multi-domain datasets. StyloAI achieves
accuracy rates of 81% and 98% on the test set of the AuTextification dataset
and the Education dataset, respectively. This approach surpasses the
performance of existing state-of-the-art models and provides valuable insights
into the differences between AI-generated and human-authored texts.

该研究提出了 StyloAI，一种基于数据驱动的模型，通过在两个多领域数据集上应用随机森林分类器使用 31 个文体特征来识别人工智能生成的文本，该方法在 AuTextification 数据集的测试集和教育数据集上分别取得了 81% 和 98% 的准确率，并提供了人工智能生成文本和人类撰写文本之间差异的有价值的见解。