Editorial: Generative artificial intelligence as a plagiarism problem
Abstract
There is increasing concern and consternation about generative artificial intelligence (AI) programs and its potential impact on academia. This editorial addresses the potential impact of such programs on scientific publishing as it relates to the journal Biological Psychology. Using chatGPT as an example, it makes the case that a prime concern is its implications for facilitating plagiarism. It briefly outlines what is known about the algorithm of the GPT text model, and also the implications of its chatGPT front end, on being able to establish appropriate credit for ideas in text that it outputs. It is concluded that, at least for Biological Psychology, the expectation is that authors will be transparent about AI usage, will declare when AI is the source of an idea, and will redouble efforts to seek out and cite prior claims to ideas in the published literature when AI is involved.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Currently, there appears to be no effective working solution to the issue of generative AI sourcing ideas from unpublished online materials without proper attribution.
“Currently, there appears to be no effective working solution to this issue (Dien, 2023).”
From GenAI et al.: Cocreation, Authorship, Ownership, Academic Ethics and Integrity in a Time of Generative AI (2024) · cites this paper as Dien, 2023
One of the primary concerns with generative AI is its ability and the degree to source ideas from unpublished online materials without proper attribution.
“One of the primary concerns with generative AI is its ability and the degree to source ideas from unpublished online materials without proper attribution (Dien, 2023;Weissman, 2023).”
From GenAI et al.: Cocreation, Authorship, Ownership, Academic Ethics and Integrity in a Time of Generative AI (2024) · cites this paper as Dien, 2023
Cites
ELIZA—a computer program for the study of natural language communication between man and machine
Weizenbaum, J. (1966) · Communications of the ACM · doi:10.1145/365153.365168 · Cited by 4,452 · see citing works
Lund, B. D., Wang, T., Mannuru, N. R., Nie, B., Shimray, S., & Wang, Z. (2023) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.24750 · Cited by 919 · see citing works
Algebraic Structures in Natural Language
Lappin, S., & Bernardy, J.-P. (2022) · doi:10.1201/9781003205388 · Cited by 21 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Lee, D., Arnold, M., Srivastava, A., Plastow, K., Strelan, P., Ploeckl, F., Lekkas, D., & Palmer, E. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100221 · Cited by 402 · see citing works
Bozkurt, A. (2024) · Open Praxis · doi:10.55982/openpraxis.16.1.654 · Cited by 215 · see citing works
Akiba, D., & Fraboni, M. C. (2023) · Education Sciences · doi:10.3390/educsci13090885 · Cited by 115 · see citing works
Ethical Use of Artificial Intelligence for Scientific Writing: Current Trends
Chetwynd, E. (2024) · Journal of Human Lactation · doi:10.1177/08903344241235160 · Cited by 62 · see citing works
Plagiarism, Academic Ethics, and the Utilization of Generative AI in Academic Writing
Koplin, J., & Philosophy Documentation Center (2023) · International Journal of Applied Philosophy · doi:10.5840/ijap2023372202 · Cited by 13 · see citing works
Halliday, S., Lavis, T., Callaghan, P., & Chur-Hansen, A. (2026) · Australian Psychologist · doi:10.1080/00050067.2025.2580236 · Cited by 2 · see citing works
Dilber, C., & Yoşumaz, İ. (2026) · Journal of Academic Ethics · doi:10.1007/s10805-025-09681-5 · Cited by 1 · see citing works
- Authors
- Dien, J.
- Affiliations
- University of Maryland, College Park (US)
- Corresponding author
- Dien, Joseph
- ORCID
- Dien, Joseph
- Venue
- Biological Psychology
- Publisher
- Elsevier BV
- Published
- 2023-07
- Volume
- 181
- Pages
- 108621
- ISSN
- 0301-0511 (ISSN-L)
- OpenAlex
- W4381893443
- Cited by
- 53
- References
- 3
- Citations by year
- 2026: 13 · 2025: 17 · 2024: 14 · 2023: 9
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biological Psychology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Physical Sciences › Computer Science › Artificial Intelligence › Law, AI, and Intellectual Property
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Keywords
- generative AI, plagiarism, ChatGPT, scholarly publishing, authorship credit, AI disclosure
- MeSH terms
- Algorithms, Artificial Intelligence, Humans, Publishing, Plagiarism
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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