Letter to editor: Academic journals should clarify the proportion of NLP-generated content in papers

Tang, Gengyan

doi:10.1080/08989621.2023.2180359

Cited by 19 publications

(8 citation statements)

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“…Although some authors have argued that the use of ChatGPT would disadvantage non‐native English speakers because the skills of native English speakers would be amplified (Liang et al, 2023), others have argued that it would benefit them by offering a competitive advantage versus native English speakers (Huang & Tan, 2023). We note, as a curiosity, that the majority of the paper written by the latter pair of authors was in fact generated by ChatGPT, and even though this assistance was acknowledged, we side with the opinion of Tang (2023) that excessive reliance on ChatGPT, basically to substitute for an author's ability to write a scientific paper, should be considered misconduct; that is, authorship of the human authors should be invalidated since very limited intellectual reflection is involved other than screening and editing ChatGPT's output. With a striking amplification of papers partially or mostly written by ChatGPT, we confidently declare that a new war in, and on, academic publishing has now officially begun.…”

Section: Chatgpt From the Prism Of Predatory Publishing And Paper Mil...mentioning

confidence: 95%

“…However, we point to a case in which apparently fictitious ChatGPT-'created' references led to the retraction of a preprint, and the blacklisting of the authors. 4 It has also been argued that authors should declare the proportion of content that has been AI-generated and that an excessive amount could be regarded as academic misconduct (Tang, 2023). Although it is claimed that text written by ChatGPT can be detected (Cingillioglu, 2023;Desaire et al, 2023), detection will become more difficult as LLM tools develop, even with the use of watermarking (Anderson et al, 2023;Brainard, 2023).…”

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confidence: 99%

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Risks of abuse of large language models, like ChatGPT, in scientific publishing: Authorship, predatory publishing, and paper mills

Kendall,

Teixeira da Silva

2023

Learned Publishing

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Key points Academia is already witnessing the abuse of authorship in papers with text generated by large language models (LLMs) such as ChatGPT. LLM‐generated text is testing the limits of publishing ethics as we traditionally know it. We alert the community to imminent risks of LLM technologies, like ChatGPT, for amplifying the predatory publishing ‘industry’. The abuse of ChatGPT for the paper mill industry cannot be over‐emphasized. Detection of LLM‐generated text is the responsibility of editors and journals/publishers.

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Section: Chatgpt From the Prism Of Predatory Publishing And Paper Mil...mentioning

confidence: 95%

mentioning

confidence: 99%

Risks of abuse of large language models, like ChatGPT, in scientific publishing: Authorship, predatory publishing, and paper mills

Kendall,

Teixeira da Silva

2023

Learned Publishing

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“…Our prior study employed ChatGPT for a conclusion in the study “Assessing the Accuracy of ChatGPT on Core Questions in Glomerular Disease” [ 56 ]. A letter to editor suggests that academic journals should clarify the proportion of AI language model-generated content in papers, and excessive use should be considered academic misconduct [ 57 ]. Many scientists disapprove that ChatGPT can be listed as author on research papers [ 58 , 59 ].…”

Section: Ai’s Unethical Role In Scholarly Writingmentioning

confidence: 99%

Ethical Dilemmas in Using AI for Academic Writing and an Example Framework for Peer Review in Nephrology Academia: A Narrative Review

Miao,

Thongprayoon,

Suppadungsuk

et al. 2023

Clinics and Practice

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The emergence of artificial intelligence (AI) has greatly propelled progress across various sectors including the field of nephrology academia. However, this advancement has also given rise to ethical challenges, notably in scholarly writing. AI’s capacity to automate labor-intensive tasks like literature reviews and data analysis has created opportunities for unethical practices, with scholars incorporating AI-generated text into their manuscripts, potentially undermining academic integrity. This situation gives rise to a range of ethical dilemmas that not only question the authenticity of contemporary academic endeavors but also challenge the credibility of the peer-review process and the integrity of editorial oversight. Instances of this misconduct are highlighted, spanning from lesser-known journals to reputable ones, and even infiltrating graduate theses and grant applications. This subtle AI intrusion hints at a systemic vulnerability within the academic publishing domain, exacerbated by the publish-or-perish mentality. The solutions aimed at mitigating the unethical employment of AI in academia include the adoption of sophisticated AI-driven plagiarism detection systems, a robust augmentation of the peer-review process with an “AI scrutiny” phase, comprehensive training for academics on ethical AI usage, and the promotion of a culture of transparency that acknowledges AI’s role in research. This review underscores the pressing need for collaborative efforts among academic nephrology institutions to foster an environment of ethical AI application, thus preserving the esteemed academic integrity in the face of rapid technological advancements. It also makes a plea for rigorous research to assess the extent of AI’s involvement in the academic literature, evaluate the effectiveness of AI-enhanced plagiarism detection tools, and understand the long-term consequences of AI utilization on academic integrity. An example framework has been proposed to outline a comprehensive approach to integrating AI into Nephrology academic writing and peer review. Using proactive initiatives and rigorous evaluations, a harmonious environment that harnesses AI’s capabilities while upholding stringent academic standards can be envisioned.

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“…Academic journals have been quick to introduce editorial policies in response to the challenges posed by research integrity (Tang 2023a). Although some journals explicitly prohibit authors from employing AIGC, others permit its usage under the condition of appropriate disclosure.…”

Section: Introductionmentioning

confidence: 99%

A Rapid Investigation of Artificial Intelligence Generated Content Footprints in Scholarly Publications

Tang

Eaton

2023

Preprint

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This study reports on a novel phenomenon observed in scholarly publications. Some research articles unrelated to the field of artificial intelligence (AI) generate content (AIGC contain confusing phrases such as “As an AI language model...”. We conceptualize this phenomenon as “AIGC footprints”. To provide early evidence, we conducted a small-scale sample investigation by collecting 25 articles. We found that the appearance of AIGC footprints corresponds to the time when the public version of ChatGPT was launched. These 25 articles were published by authors from countries in Central Asia, South Asia, and Africa. Among these authors, there were assistant professors (n = 5), Ph.D. researcher (n = 6), as well as Ph.D. and master’s students (n = 3). Single authors (n = 16) and single affiliations (n = 23) were more common. Analysis of the article content revealed that some authors utilized ChatGPT for literature reviews (n = 11) or idea generation (n = 11). Articles with AIGC footprints are widely distributed across various professional fields, such as Communication and Media Studies (n = 3), Cybersecurity (n = 2), Civil Engineering (n = 2), and Agricultural Technology (n = 2). The 25 articles with AIGC footprints were published in 18 different academic journals. Most of the academic journals did not disclose their APCs on their websites (n = 11), nor were they indexed by Web of Science, Scopus, and DOAJ (n = 17). The emergence of AIGC footprints reflects the potential challenges faced by scholarly publishing and higher education in ensuring quality assurance, as well as indicating potential problems in research integrity. We provide several recommendations, including the development of best research practice guidelines in the context of AIGC, integrating transparent use of AIGC into higher education instruction, and fostering ethical leadership.

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Letter to editor: Academic journals should clarify the proportion of NLP-generated content in papers

Cited by 19 publications

References 4 publications

Risks of abuse of large language models, like ChatGPT, in scientific publishing: Authorship, predatory publishing, and paper mills

Risks of abuse of large language models, like ChatGPT, in scientific publishing: Authorship, predatory publishing, and paper mills

Ethical Dilemmas in Using AI for Academic Writing and an Example Framework for Peer Review in Nephrology Academia: A Narrative Review

A Rapid Investigation of Artificial Intelligence Generated Content Footprints in Scholarly Publications

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