Will ChatGPT get you caught? Rethinking of Plagiarism Detection (2302.04335v1)

Abstract: The rise of AI technology and its impact on education has been a topic of growing concern in recent years. The new generation AI systems such as chatbots have become more accessible on the Internet and stronger in terms of capabilities. The use of chatbots, particularly ChatGPT, for generating academic essays at schools and colleges has sparked fears among scholars. This study aims to explore the originality of contents produced by one of the most popular AI chatbots, ChatGPT. To this end, two popular plagiarism detection tools were used to evaluate the originality of 50 essays generated by ChatGPT on various topics. Our results manifest that ChatGPT has a great potential to generate sophisticated text outputs without being well caught by the plagiarism check software. In other words, ChatGPT can create content on many topics with high originality as if they were written by someone. These findings align with the recent concerns about students using chatbots for an easy shortcut to success with minimal or no effort. Moreover, ChatGPT was asked to verify if the essays were generated by itself, as an additional measure of plagiarism check, and it showed superior performance compared to the traditional plagiarism-detection tools. The paper discusses the need for institutions to consider appropriate measures to mitigate potential plagiarism issues and advise on the ongoing debate surrounding the impact of AI technology on education. Further implications are discussed in the paper.

Plagiarism Detection in AI-Generated Content: An Analysis of ChatGPT

The paper "Will ChatGPT get you caught? Rethinking of Plagiarism Detection" by Mohammad Khalil and Erkan Er presents a thorough investigation into the capabilities of AI chatbots, specifically ChatGPT, to generate content that evades conventional plagiarism detection mechanisms. As artificial intelligence evolves, its impact on the educational landscape, particularly in relation to academic integrity and plagiarism concerns, warrants rigorous analysis.

Study Design and Methodology

The authors conducted an empirical paper analyzing 50 essays produced by ChatGPT in response to various open-ended prompts. These essays were subjected to plagiarism checks using iThenticate and Turnitin, two widely recognized software tools in academic settings. The methodology was designed to explore the originality scores of AI-generated content, thereby assessing the effectiveness of traditional plagiarism checkers in identifying these machine-generated texts.

Key Findings

The results indicate notable originality in the majority of ChatGPT-generated essays, with iThenticate reporting that 68% of essays had a similarity score of less than 10%. Turnitin reported slightly higher average similarity scores. Importantly, ChatGPT itself successfully identified its own generated content with over 92% accuracy—a significant improvement over the traditional plagiarism-detection tools. This discrepancy raises important concerns about the adequacy of current plagiarism detection methods when applied to AI-created work.

Implications

The findings of this paper have profound implications for educational institutions, necessitating urgent adaptation of policies related to academic integrity and AI usage. Given ChatGPT's ability to produce content that is practically indistinguishable from human-generated text, institutions face challenges in ensuring genuine student submissions. This also poses questions regarding reliance on existing plagiarism detection tools that may not be effective against AI-generated content.

Future Directions and Recommendations

To mitigate potential academic misconduct involving AI tools, institutions must embrace a dual approach in plagiarism detection: verification of content origin alongside traditional model similarity checks. Moreover, educators are advised to craft assignments that promote critical thinking and personal reflection, thus diminishing the plausibility of accepting AI-generated content as genuine student work. AI systems themselves could be employed more aggressively to verify the origin of suspected submissions.

In conclusion, this paper lays the groundwork for further exploration into AI's capabilities in educational settings and highlights the dynamic challenges it presents to academic integrity. As AI continues to advance, addressing these challenges, proactively adapting policy measures, and enhancing detection mechanisms are imperative to uphold the quality and credibility of education systems worldwide.