  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 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 consonants, word stress, nouns, verbs,
pronouns, direct objects, 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 capacity of AI for producing more human-like text.
