Exploring the capacity for textual production and meanings between humans and AI
a comparative study of academic abstracts
DOI:
https://doi.org/10.14393/DLv18a2024-35Keywords:
Artificial Intelligence, Text Linguistics, Textualization, Meanings, AbstractAbstract
Recently, the popularization of some Artificial Intelligence (AI) tools in Brazil, such as ChatGPT (Generative Pre-trained Transformer), and the increasing waves of similar tools being used in digital environments for text production and/or revision or virtual assistance (Google Assistant, Alexa, Siri, Bixby) have sparked a debate and highlighted an innovative yet controversial movement, with complicating factors and negative aspects (related to copyright issues) that seems irreversible. Supporting this debate, this study focuses on a comparative analysis between abstracts produced by students/academics and texts generated by artificial intelligence (AI) - ChatGPT. The descriptive and explanatory research aims to identify how textual elements, such as semantic, compositional, and enunciative components, show disparities between the two types of production. The corpus comprised three academic abstracts, one generated by ChatGPT and two produced by academics. The exploration of the texts allowed for experimentation regarding the textual production capabilities of humans and AI, as well as the identification of elements that differentiate them. Considering the same prompt/command statement, the results demonstrated similarities in linguistic usage to indicate argumentative orientation and enunciative stances, such as forms of referencing or citation, but differences when considering a text plan for an academic abstract that includes elements such as theme, objective, genre, and defense of the base text's point of view.
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