Assessing Textual Conformity and Originality in AI-Generated Content: An Analytical Approach

Abstract

The rapid increase in the use of artificial intelligence (AI) has also been seen in the generation of texts in various fields, from academic papers to marketing content. At the same time, there is a growing need for efficient and accurate comparison between AI-generated texts in terms of form and content. Using a screening design of experiment, this contribution compares the influence of selected factors on the similarity and originality of texts generated by artificial intelligence. The response is the result of a formal comparison of the agreement of the texts generated by two anti-plagiarism programs commonly used to check the originality of diploma theses. The used method, with a certain degree of reliability, points to the influence of various factors on the originality of texts generated in this way and provides a new insight into the dynamics of textual creativity and innovation in the era of artificial intelligence. It is a helpful tool for researchers, educators and professionals from various fields who want to ensure that the texts produced by the user interface are original and do not violate copyright.