A Preliminary Investigation of Fake Peer-Reviewed Citations and References Generated by ChatGPT

Day, Terence

doi:10.1080/00330124.2023.2190373

Cited by 78 publications

(36 citation statements)

References 13 publications

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“…But one of the sources was allegedly published in 2011 and all three were fake references! This is consistent with previous reports of ChatGPT citing fake literature (Day, 2023). In fact, one study found that out of 50 apparent sources, 66% were fake (Haman & Školník, 2023).…”

Section: Chatgpt Assistance To Geographerssupporting

confidence: 92%

“…Other applications for ChatGPT could be covered, such as extensions for optical character recognition (converting an image into text). Fake references generated by ChatGPT can also be used to flag the possibility of plagiarised work (Day, 2023). However, it is important to close with ethical considerations -not least because this was self-identified as the most important question surrounding the application of ChatGPT to (geographic) teaching and research.…”

Section: Chatgpt Assistance To Geographersmentioning

confidence: 99%

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AI literacy in geographic education and research: Capabilities, caveats, and criticality

Wilby,

Esson

2023

Geographical Journal

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Concerns about runaway artificial intelligence (AI) – including large language models (LLMs) like ChatGPT – are at the forefront of contemporary political, social, and scientific discourse. This commentary provides a first look at ChatGPT's capabilities and limitations in supporting geographic research, critical thinking, learning, and curriculum development. We assessed ChatGPT's geographic knowledge, synthesising abilities, and potential for extrapolation. ChatGPT was employed for writing assistance, research evaluation, curriculum material creation, and content generation. Despite achieving scores of 47% to 55% on an actual exam paper, ChatGPT exhibited shortcomings including the generation of false references. Ethical concerns regarding academic misconduct, model bias, robustness, and toxic output were also identified. We assert that AI and LLMs like ChatGPT have transformative potential in Geography education and knowledge production but demand critical usage. Accordingly, we urge geographers to enhance AI literacy to enable responsible and effective use of these assistive technologies in our academic practice.

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Section: Chatgpt Assistance To Geographerssupporting

confidence: 92%

Section: Chatgpt Assistance To Geographersmentioning

confidence: 99%

AI literacy in geographic education and research: Capabilities, caveats, and criticality

Wilby,

Esson

2023

Geographical Journal

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“…Another issue that we did not cover, but may become more pertinent as the gender debate in academia widens, is RTBF in the context of gender transition (Correia et al, 2021;Korenhof & Koops, 2014). Finally, considering that generative artificial intelligence, for example ChatGPT, is able to generate fictitious citations (Day, 2023), which is a form 14 https://pubpeer.com/ of misinformation, authors whose names might appear in such fabricated citations might want to have the Right to retract false citations. In this case, the right to retract fake references from the public record might serve as a novel instrument for protecting academic and personal integrity, provided that journals and publishers provide a suitable framework in which such a right can be put into practice.…”

Section: Discussionmentioning

confidence: 99%

Can the principle of the ‘right to be forgotten’ be applied to academic publishing? Probe from the perspective of personal rights, archival science, open science and post‐publication peer review

Teixeira da Silva,

Nazarovets

2023

Learned Publishing

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In this paper, we reflect on how the principle of the ‘right to be forgotten’ (RTBF), specifically the right to erasure as enshrined in Article 17 (and to some extent Art. 19 and Art. 21) of the General Data Protection Regulation (GDPR; Regulation (EU) 2016/679), or the right to delete undesirable, unflattering or reputation‐damaging archived records of oneself from search engines or databases, might apply to academic publishing. In particular, we focus on archival (library and information) science, post‐publication peer review, and reflect on whether RTBF is compatible with open science principles. Even though RTBF became enshrined in EU law in 2018, its trans‐Atlantic export to the United States faces resistance because it is seen as being incompatible with First Amendment rights. We ponder the pertinence of the debate regarding local versus global applicability of RTBF when considering the transnational nature of some collaborative research. Although RTBF applies broadly to search engines such as Google, we question whether authors have this right and also whether publishers are subjected to this law with respect to science databases, or even ‘local’ (i.e., publisher‐controlled) archives, especially in the light of retractions or withdrawals, in which data and files are removed from a preprint or journal's website or, in extreme cases, where all or most bibliometric information is scrubbed clean, as in the case of ‘silent retractions’. We extend our reflections further to appreciate whether authors or editors are entitled to RTBF in extreme instances of misconduct or fraud. The fundamental right to privacy and personal choice, as is suggested by (or enshrined in) RTBF, is not—in our view—compatible with several principles related to the integrity of data and information, or even their preservation, and may be diametrically opposed, depending on the situation. We encourage wider debate on this budding pertinent issue as a fundamental aspect of academic rights and freedoms.

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“…little relationship reality in a phenomenon sometimes referred to as "hallucinations" (12,13). In particular, ChatGPT may generate text complete with appropriate-sounding but completely fictional citations included (14). It is obvious that articles containing factual inaccuracies, invented citations, and plagiarized content do not meet the editorial standards of our journals.…”

mentioning

confidence: 99%

Generative AI: Potential and Pitfalls in Academic Publishing

Silverman,

Ali,

Rybak

et al. 2023

JPGN Reports

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G enerative artificial intelligence (AI) has attracted enormous attention since the release of Chat-GPT (1) in late 2022. Other generative AI chatbots used to generate text (including Bard, Claude, and CoPilot (2-4)) and images (including Dall-E, Midjourney, and Stable Diffusion (5-7)) have likewise seen a remarkable explosion in development and uptake. While ChatGPT has been promoted for its potential to assist users in efficiently and easily creating text to serve a wide range of purposes, this editorial focuses on the journal's opinion on the use of generative AI technology in creating articles submitted to this journal.ChatGPT utilizes a technology known as a generative pretrained transformer large language model (8). This is a form of machine learning in which very large language-based data sets are used to train computers to comprehend natural language. While natural language processing is not new, ChatGPT is currently unique in its ability to not only understand queries and information to which it has access, but also to generate new, comprehensive, and fluent language-based content. Models, such as ChatGPT, which generates language, and Dall-E, Midjourney, or Stable Diffusion, which all generate images, are collectively referred to as "generative AI", and can be seen as marking a dramatic shift in both the capabilities and widespread access to AI technology.Since its release on November 30, 2022, ChatGPT achieved the most rapid adoption of a consumer software application in history by amassing over 100 million users by January 2023 (9). Users have leveraged ChatGPT to write software, song lyrics, stories, poems, and letters. With its ability to recall previous prompts within a conversation, users can fine-tune its responses to modify the content or tone of the content it generates. The underlying model used to generate content is continuously improved through feedback from users. While users easily identified flaws in the responses provided by the earlier GPT-3 version, the model has iterated quickly. GPT-4, OpenAI's latest effort in scaling up deep learning, has been described by its creators to exhibit "human-level performance on various professional and academic benchmarks" (10). It has demonstrated impressive abilities in passing standardized examinations including the Law School Admission Test, Scholastic Aptitude Test, a unified bar exam, and even the United States Medical Licensing Exam (10).ChatGPT, and other large language model-based applications, use large data sets consisting of text available on the web. Sources may include articles, books, web-based advertising, and social media posts. ChatGPT offers several exciting and desirable potential benefits, including its potential to make completing written articles more quickly as well as completing literature review summaries. With its ability to help users write in English fluently, it has been touted as a way to help make academic publishing more equitable and diverse (11). The time saved in summarizing data and generating articles could help r...

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A Preliminary Investigation of Fake Peer-Reviewed Citations and References Generated by ChatGPT

Cited by 78 publications

References 13 publications

AI literacy in geographic education and research: Capabilities, caveats, and criticality

AI literacy in geographic education and research: Capabilities, caveats, and criticality

Can the principle of the ‘right to be forgotten’ be applied to academic publishing? Probe from the perspective of personal rights, archival science, open science and post‐publication peer review

Generative AI: Potential and Pitfalls in Academic Publishing

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