Does GPT-3 qualify as a co-author of a scientific paper publishable in peer-review journals according to the ICMJE criteria? A case study

Osmanovic-Thunström, Almira; Steingrímsson, Steinn

doi:10.1007/s44163-023-00055-7

Cited by 12 publications

(3 citation statements)

References 19 publications

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“…making significant contributions from initial conception to final production. [30] This two-dimensional framework uncovers the layers of AI's potential in academic collaborations. It ranges from routine task-oriented applications to AI's burgeoning capacity to foster innovative thought and critical reasoning.…”

Section: Collaboration Frameworkmentioning

confidence: 97%

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Assessing GPT-4’s Role as a Co-Collaborator in Scientific Research: A Case Study Analyzing Einstein’s Special Theory of Relativity

Bryant

2023

Preprint

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This paper investigates GPT-4’s role as a research partner, particularly its ability to scrutinize complex theories like Einstein’s Special Relativity Theory (SRT). GPT-4’s advanced capabilities prove invaluable in complex research scenarios where human expertise might be limited. Despite initial biases, an inclination to uphold Einstein’s theory, and certain mathematical limitations, GPT-4 validated an inconsistency within the SRT equations, leading to a questioning of the theory's overall validity. GPT-4 contributed significantly to honing the analytical approach and expanding constraints. This paper explores the strengths and challenges associated with the use of GPT-4 in scientific research, with a strong emphasis on the need for vigilance concerning potential biases and limitations in large language models. The paper further introduces a categorization framework for AI collaborations, and specific guidelines for optimal interaction with advanced models like GPT-4. Future research endeavors should focus on augmenting these models’ precision, trustworthiness, and impartiality, particularly within complex or contentious research domains.

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Section: Collaboration Frameworkmentioning

confidence: 97%

“…Osmanovic-Thunström and Steingrimsson showed that GPT-3 can be considered a co-author in their study, emphasizing GPT-3's potential to contribute to scientific work with minimal human intervention. [30] This work transcends their concept by engaging GPT-4 as an advanced research partner.…”

Section: Related Workmentioning

confidence: 99%

Assessing GPT-4’s Role as a Co-Collaborator in Scientific Research: A Case Study Analyzing Einstein’s Special Theory of Relativity

Bryant

2023

Preprint

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“…In a blinded, randomized, noninferiority controlled study, GPT-4 was found to be equal to humans in writing introductions regarding publishability, readability, and content quality [ 52 ]. An article using GPT-3 to write a review on “effects of sleep deprivation on cognitive function” demonstrated ChatGPT’s adherence to ICMJE co-authorship criteria, including conception, drafting, and accountability [ 53 ]. However, it revealed challenges with accurate referencing.…”

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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The impact of AI on the post‐pandemic generation of early career researchers: What we know or can predict from the published literature

Herman,

Nicholas,

Abrizah

et al. 2024

Learned Publishing

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This extensive literature review is not a stand‐alone paper, as it was conducted to help set the scene for the third and current stage of the Harbinger of Change project (H‐3), which is focusing on the impact of artificial intelligence (AI) on early career researchers (ECRs). Its purpose is to inform the design, scope and question‐forming of the ongoing interview project (2024–). The overarching aim of the review is to establish what we know of the already extant and/or predicted opportunities and challenges that AI‐driven technologies present to researchers, in general, and the cohort of junior researchers among them, in particular. It was found that very little empirical evidence exists of what is happening to ECRs on the ground, and that tends to be drowned in a sea of forecasts and prognostications. However, down the road there are clear benefits accruing to ECRs and, arguably, the most appealing for novice researchers must be the benefits of enhancing their productivity, the key to all scholarly rewards, inclusive of career advancement.

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Does GPT-3 qualify as a co-author of a scientific paper publishable in peer-review journals according to the ICMJE criteria? A case study

Cited by 12 publications

References 19 publications

Assessing GPT-4’s Role as a Co-Collaborator in Scientific Research: A Case Study Analyzing Einstein’s Special Theory of Relativity

Assessing GPT-4’s Role as a Co-Collaborator in Scientific Research: A Case Study Analyzing Einstein’s Special Theory of Relativity

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

The impact of AI on the post‐pandemic generation of early career researchers: What we know or can predict from the published literature

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