The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Plagiarism in the age of massive Generative Pre-trained Transformers (GPT-3)
Open accessAbstract
As if 2020 was not a peculiar enough year, its fifth month saw the relatively quiet publication of a preprint describing the most powerful natural language processing (NLP) system to date—GPT-3 (Generative Pre-trained Transformer-3)—created by the Silicon Valley research firm OpenAI. Though the software implementation of GPT-3 is still in its initial beta release phase, and its full capabilities are still unknown as of the time of this writing, it has been shown that this artificial intelligence can comprehend prompts in natural language, on virtually any topic, and generate relevant original text content that is indistinguishable from human writing. Moreover, access to these capabilities, in a limited yet worrisome enough extent, is available to the general public. This paper presents examples of original content generated by the author using GPT-3. These examples illustrate some of the capabilities of GPT-3 in comprehending prompts in natural language and generating convincing content in response. I use these examples to raise specific fundamental questions pertaining to the intellectual property of this content and the potential use of GPT-3 to facilitate plagiarism. The goal is to instigate a sense of urgency, as well as a sense of present tardiness on the part of the academic community in addressing these questions.
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“This means that students could potentially use these systems to cheat on their assignments by submitting essays that are not their own work (e.g.Dehouche, 2021).”
From Chatting and cheating: Ensuring academic integrity in the era of ChatGPT (2024) · cites this paper as Dehouche, 2021
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“The fact that AI is trained with existing work and its ability to quickly generate content that may be unauthorized imitations impose fundamental challenges to the regulation of plagiarism and academic integrity [3,4].”
From AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities (2024) · cites this paper as [3]
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“This is due to concern centered on plagiarism because it is challenging to trace and verify the originality of AI-generated content [59, 60].”
From Generative artificial intelligence (GAI) usage guidelines for scholarly publishing: a cross-sectional study of medical journals (2025) · cites this paper as [60]
In the citing paper
“The public discourse surrounding GenAI has been mostly positive, but in the education sector there is serious concern about academic integrity and plagiarism (Dehouche, 2021;Lampropoulos et al., 2023;Sullivan et al., 2023;Yeo, 2023).”
From Not quite eye to A.I.: student and teacher perspectives on the use of generative artificial intelligence in the writing process (2023) · cites this paper as Dehouche, 2021
In the citing paper
“Finally, one last threat may be posed by human and artificial works being indistinguishable (Dehouche, 2021).”
From On the creativity of large language models (2025) · cites this paper as Dehouche, 2021
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Citations
Cites
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Cited by
Sorted by citations
ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · doi:10.35542/osf.io/5er8f · Cited by 7,552
ChatGPT for good? On opportunities and challenges of large language models for education
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · Learning and Individual Differences · doi:10.1016/j.lindif.2023.102274 · Cited by 7,326
“It is becoming increasingly difficult to distinguish whether a text is machine-or human-generated, presenting an additional major challenge to teachers and educators [51, 52, 53, 54].”
BackgroundChatting and Cheating. Ensuring academic integrity in the era of ChatGPT
Cotton, D., Cotton, P., & Shipway, J. R. (2023) · doi:10.35542/osf.io/mrz8h · Cited by 3,079
Chatting and cheating: Ensuring academic integrity in the era of ChatGPT
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024) · Innovations in Education and Teaching International · doi:10.1080/14703297.2023.2190148 · Cited by 3,087
ChatGPT: Bullshit spewer or the end of traditional assessments in higher education?
(2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.1.9 · Cited by 1,806
Metadata
- Authors
- Dehouche, N.
- Affiliations
- Mahidol University (TH)
- Corresponding author
- Dehouche, N
- ORCID
- Dehouche, N
- Venue
- Ethics in Science and Environmental Politics
- Publisher
- Inter-Research Science Center
- Published
- 2021-03-25
- Volume
- 21
- Pages
- 17-23
- ISSN
- 1611-8014 (ISSN-L)
- 1863-5415
- OpenAlex
- W3125358881
- Cited by
- 296
- References
- 25
- Citations by year
- 2026: 24 · 2025: 67 · 2024: 87 · 2023: 98 · 2022: 12 · 2021: 8
- FWCI
- 64.07
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- public-domain
- creativecommons.org/licenses/by/4.0/ (vor)
- Locations
- Ethics in Science and Environmental Politics (publishedVersion, public-domain)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- PhilPapers (PhilPapers Foundation) (submittedVersion)
- Funders
- Mahidol University International College
- University of Oxford
- Mahidol University
- Région Normandie
- Topics
- Social Sciences › Education › Academic integrity and plagiarism
- Physical Sciences › Computer Science › Artificial Intelligence › Law, AI, and Intellectual Property
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Keywords
- plagiarism, GPT-3, generative pre-trained transformer, large language models, intellectual property, academic integrity, AI-generated text
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