While extensive research has focused on ChatGPT in recent years, very few studies have systematically quantified and compared linguistic features between human-written and artificial intelligence (AI)-generated language. This exploratory study aims to investigate how various linguistic components are represented in both types of texts, assessing the ability of AI to emulate human writing. Using human-authored essays as a benchmark, we prompted ChatGPT to generate essays of equivalent length. These texts were analyzed using Open Brain AI, an online computational tool, to extract measures of phonological, morphological, syntactic, and lexical constituents. Despite AI-generated texts appearing to mimic human speech, the results revealed significant differences across multiple linguistic features such as specific types of consonants, nouns, adjectives, pronouns, adjectival/prepositional modifiers, and use of difficult words, among others. These findings underscore the importance of integrating automated tools for efficient language assessment, reducing time and effort in data analysis. Moreover, they emphasize the necessity for enhanced training methodologies to improve the engineering capacity of AI for producing more human-like text.

翻译：尽管近年来针对ChatGPT的研究广泛开展，但鲜有研究系统性地量化并比较人类撰写与人工智能生成语言之间的语言学特征。本探索性研究旨在调查各类语言成分在两种文本中的表征方式，评估AI模仿人类写作的能力。以人类撰写的论文作为基准，我们通过ChatGPT生成长度相当的论文。利用在线计算工具Open Brain AI对这些文本进行分析，提取音位、形态、句法和词汇构成要素的度量指标。尽管AI生成的文本看似模仿人类语言，但结果显示在多个语言特征上存在显著差异，包括特定类型的辅音、名词、形容词、代词、形容词/介词修饰语以及复杂词汇的使用等方面。这些发现凸显了整合自动化工具以实现高效语言评估的重要性，可显著减少数据分析的时间与精力。此外，研究结果强调需要改进训练方法以提升AI生成更类人文本的工程能力。