Étiquette : Generative Artificial Intelligence

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Generative AI and the future of scientometrics: current topics and future questions

Authors : Benedetto Lepori, Jens Peter Andersen, Karsten Donnay

The aim of this paper is to review the use of GenAI in scientometrics, and to begin a debate on the broader implications for the field. First, we provide an introduction on GenAI’s generative and probabilistic nature as rooted in distributional linguistics.

And we relate this to the debate on the extent to which GenAI might be able to mimic human ‘reasoning’. Second, we leverage this distinction for a critical engagement with recent experiments using GenAI in scientometrics, including topic labelling, the analysis of citation contexts, predictive applications, scholars’ profiling, and research assessment.

GenAI shows promise in tasks where language generation dominates, such as labelling, but faces limitations in tasks that require stable semantics, pragmatic reasoning, or structured domain knowledge. However, these results might become quickly outdated. Our recommendation is, therefore, to always strive to systematically compare the performance of different GenAI models for specific tasks.

Third, we inquire whether, by generating large amounts of scientific language, GenAI might have a fundamental impact on our field by affecting textual characteristics used to measure science, such as authors, words, and references. We argue that careful empirical work and theoretical reflection will be essential to remain capable of interpreting the evolving patterns of knowledge production.

DOI : https://doi.org/10.48550/arXiv.2507.00783

 

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Generative AI and Open Access Publishing: A New Economic Paradigm

Authors : Leo S. Lo

The integration of generative artificial intelligence (AI) in scholarly publishing presents both opportunities and challenges for open access. AI can streamline workflows, reduce costs, and enhance the discoverability of research, potentially making open access more financially sustainable.

However, the same AI capabilities also raise concerns about exclusivity and the creation of a tiered system that limits access to knowledge. Publishers face a strategic decision between embracing open access and leveraging AI for proprietary content and services.

Libraries play a crucial role in advocating for open access and ethical AI use, building expertise, and influencing policy development. Balancing the benefits of AI with the principles of equity and inclusivity requires collaboration among stakeholders.

By working together, publishers, librarians, and policymakers can harness the power of AI to democratize access to knowledge while upholding ethical standards, fostering a more inclusive and equitable academic community.

URL : Generative AI and Open Access Publishing: A New Economic Paradigm

DOI : https://dx.doi.org/10.1353/lib.2025.a961190

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And Plato met ChatGPT: an ethical reflection on the use of chatbots in scientific research writing, with a particular focus on the social sciences

Authors : Reyes Calderon, Francisco Herrera

This interdisciplinary paper analyzes the use of Large Language Models based chatbots (LLM-chatbots), with ChatGPT the most known exponent, in scientific research writing. By interacting with LLM-chatbots, researchers could reduce efforts and costs as well as improve efficiency, but taking important risks, limitations, and weaknesses, which could highly-order erosion scientific thought.

While many scientific journals, as well as major publishers such as Springer-Nature or Taylor & Francis, are restricting its use, others advocate for its normalization. Debate focuses on two main questions: the possible authorship of LLM-chatbots, which is majority denied because their inability to meet the required standards; and the acceptance of hybrid articles (using LLM-chatbots).

Very recently, focusing on the education area, literature has found analogical similarities between some issues involved in Chatbots and that of Plato criticisms of writing, contained in the Phaedrus. However, the research area has been neglected. Combining philosophical and technological analysis, we explore Plato’s myth of Theuth and Thamus, questioning if chatbots can improve science. From an interdisciplinary perspective, and according with Plato, we conclude LLM-chatbots cannot be considered as authors in a scientific context.

Moreover, we offer some arguments and requirements to accept hybrid articles. We draw attention to the need for social science publishers, an area where conceptual hypotheses can take a long time to confirm, rather than solely on experimental observations. Finally, we advocate that publishers, communities, technical experts, and regulatory authorities collaborate to establish recommendations and best practices for chatbot use.

URL : And Plato met ChatGPT: an ethical reflection on the use of chatbots in scientific research writing, with a particular focus on the social sciences

DOI : https://doi.org/10.1057/s41599-025-04650-0

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Tailoring Scientific Knowledge: How Generative AI Personalizes Academic Reading Experiences

Author : Anna Małgorzata Kamińska

The scientific literature is expanding at an unprecedented pace, making it increasingly difficult for researchers, students, and professionals to extract relevant insights efficiently.

Traditional academic publishing offers static, one-size-fits-all content that does not cater to the diverse backgrounds, expertise levels, and interests of readers. This paper explores how generative AI can dynamically personalize scholarly content by tailoring summaries and key takeaways to individual user profiles.

Nine scientific articles from a single journal issue were used to create the dataset, and prompt engineering was applied to generate tailored insights for exemplary personas: a digital humanities and open science researcher, and a mining and raw materials industry specialist. The effectiveness of AI-generated content modifications in enhancing readability, comprehension, and relevance was evaluated.

The results indicate that generative AI can successfully emphasize different aspects of an article, making it more accessible and engaging to specific audiences. However, challenges such as content oversimplification, potential biases, and ethical considerations remain.

The implications of AI-powered personalization in scholarly communication are discussed, and future research directions are proposed to refine and optimize AI-driven adaptive reading experiences.

URL : Tailoring Scientific Knowledge: How Generative AI Personalizes Academic Reading Experiences

DOI : https://doi.org/10.3390/publications13020018

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The Origins and Veracity of References ‘Cited’ by Generative Artificial Intelligence Applications: Implications for the Quality of Responses

Author :  Dirk H. R. Spennemann

The public release of ChatGPT in late 2022 has resulted in considerable publicity and has led to widespread discussion of the usefulness and capabilities of generative Artificial intelligence (Ai) language models. Its ability to extract and summarise data from textual sources and present them as human-like contextual responses makes it an eminently suitable tool to answer questions users might ask.

Expanding on a previous analysis of the capabilities of ChatGPT3.5, this paper tested what archaeological literature appears to have been included in the training phase of three recent generative Ai language models: ChatGPT4o, ScholarGPT, and DeepSeek R1. While ChatGPT3.5 offered seemingly pertinent references, a large percentage proved to be fictitious. While the more recent model ScholarGPT, which is purportedly tailored towards academic needs, performed much better, it still offered a high rate of fictitious references compared to the general models ChatGPT4o and DeepSeek.

Using ‘cloze’ analysis to make inferences on the sources ‘memorized’ by a generative Ai model, this paper was unable to prove that any of the four genAi models had perused the full texts of the genuine references. It can be shown that all references provided by ChatGPT and other OpenAi models, as well as DeepSeek, that were found to be genuine, have also been cited on Wikipedia pages.

This strongly indicates that the source base for at least some, if not most, of the data is found in those pages and thus represents, at best, third-hand source material. This has significant implications in relation to the quality of the data available to generative Ai models to shape their answers. The implications of this are discussed.

URL : The Origins and Veracity of References ‘Cited’ by Generative Artificial Intelligence Applications: Implications for the Quality of Responses

DOI : https://doi.org/10.3390/publications13010012

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Global insights: ChatGPT’s influence on academic and research writing, creativity, and plagiarism policies

Authors : Muhammad Abid Malik, Amjad Islam Amjad, Sarfraz Aslam, Abdulnaser Fakhrou

Introduction: The current study explored the influence of Chat Generative Pre-Trained Transformer (ChatGPT) on the concepts, parameters, policies, and practices of creativity and plagiarism in academic and research writing.

Methods: Data were collected from 10 researchers from 10 different countries (Australia, China, the UK, Brazil, Pakistan, Bangladesh, Iran, Nigeria, Trinidad and Tobago, and Turkiye) using semi-structured interviews. NVivo was employed for data analysis.

Results: Based on the responses, five themes about the influence of ChatGPT on academic and research writing were generated, i.e., opportunity, human assistance, thought-provoking, time-saving, and negative attitude. Although the researchers were mostly positive about it, some feared it would degrade their writing skills and lead to plagiarism. Many of them believed that ChatGPT would redefine the concepts, parameters, and practices of creativity and plagiarism.

Discussion: Creativity may no longer be restricted to the ability to write, but also to use ChatGPT or other large language models (LLMs) to write creatively. Some suggested that machine-generated text might be accepted as the new norm; however, using it without proper acknowledgment would be considered plagiarism. The researchers recommended allowing ChatGPT for academic and research writing; however, they strongly advised it to be regulated with limited use and proper acknowledgment.

URL : Global insights: ChatGPT’s influence on academic and research writing, creativity, and plagiarism policies

DOI : https://doi.org/10.3389/frma.2024.1486832

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The impact of generative AI on the scholarly communications of early career researchers: An international, multi-disciplinary study

Authors : David Nicholas, Marzena Swigon, David Clark, Abdullah Abrizah, Jorge Revez, Eti Herman, Blanca Rodríguez Bravo, Jie Xu, Anthony Watkinson

The Harbingers study of early career researchers (ECRs), their work life and scholarly communications, began by studying generational—Millennial—change (c.2016), then moved to pandemic change (c.2020) and is now investigating another potential agent of change: artificial intelligence (2024–). We report here on a substantial scoping pilot study that looks at the impact of AI on the scholarly communications of international ECRs and, extends this to the arts and humanities.

It aims to fill the knowledge gap concerning ECRs whose millennial mindset may render them especially open to change and, as the research workhorses they are, very much in the frontline. The data was collected via in-depth interviews in China, Malaysia, Poland, Portugal, Spain and (selectively) the United Kingdom/United States. The data show ECRs to be thinking, probing and, in some cases, experimenting with AI.

There was a general acceptance that AI will be responsible for the growth of low-quality scientific papers, which could lead to a decline in the quality of research. Scholarly integrity and ethics were a big concern with issues of authenticity, plagiarism, copyright and poor citation practices raised. The most widespread belief was AI would prove to be a transformative force and would exacerbate existing scholarly disparities and inequalities.

URL : The impact of generative AI on the scholarly communications of early career researchers: An international, multi-disciplinary study

DOI : https://doi.org/10.1002/leap.1628