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Will ChatGPT get you caught? Rethinking of Plagiarism Detection

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arxiv 2302.04335 v1 pith:3BNAAD7U submitted 2023-02-08 cs.AI

classification cs.AI
keywords chatgptplagiarismchatbotsessaysoriginalitywerecaughtcheck
verification ladder T0 review T1 audit T2 compute T3 formal
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The rise of Artificial Intelligence (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.

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  1. Evaluating Software Plagiarism Detection in the Age of AI: Automated Obfuscation and Lessons for Academic Integrity

    cs.SE 2025-05 conditional novelty 5.0 of 10

    Combining Token Sequence Normalization and Subsequence Match Merging substantially improves JPlag's resilience to automated obfuscation, including AI-based rewriting, without raising false-positive rates.

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