Will ChatGPT get you caught? Rethinking of Plagiarism Detection
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Abstract (arXiv)
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.
Key facts. Cited by 41 papers in the map (data through 7 Oct 2026). Builds on 0 of its 23 references that are in the map. First posted on arXiv 8 Feb 2023.
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Citing papers per year: 2023: 27; 2024: 11; 2025: 2; 2026: 1.
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- 2023The Imitation Game: Detecting Human and AI-Generated Texts in the Era of ChatGPT and BARD22 Jul 2023
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12 most cited of 41 All 41 (JSON)
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- 2024Applying IRT to Distinguish Between Human and Generative AI Responses to Multiple-Choice Assessments28 Nov 2024
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- 2024Humanizing the Machine: Proxy Attacks to Mislead LLM Detectors25 Oct 2024
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- 2024The Battle of LLMs: A Comparative Study in Conversational QA Tasks28 May 2024
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12 newest of 41 All 41 (JSON)