Étiquette : Artificial intelligence

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EN

Assessing open access scholarly journals for integration into artificial intelligence research assistants

Authors : Sanja Gidakovic, Heather Moulaison-Sandy, Jenny Bossalle

Introduction

Freely available standalone AI research assistants such as Elicit and Consensus are used by academics to find relevant literature. These systems rely extensively on freely available sources, including open access journal content. No baseline for understanding the level of quality of such journals used in these assistants has been carried out.

Method

A sample of 807 English-language journals from the Directory of Open Access Journals that became open access before 2021 was investigated for quality metrics using SCImago rankings and other defining characteristics and analysed in conjunction with the Directory data.

Analysis

Scimago journal ranking quartile scores were recorded for each of the journals. Descriptive statistics were produced using Excel, and visualizations using Tableau Public.

Results

Of our sample, over half were ranked in Scopus, and many were in quartile 1. Many university or small association journals were unranked.

Conclusions

AI research assistants may miss some high-quality open access content due to reliance on metrics. Commercial enterprises play a large role in sources used to produce content, effectively gatekeeping the process and potentially shaping the creation of new knowledge.

URL : Assessing open access scholarly journals for integration into artificial intelligence research assistants

DOI : https://doi.org/10.47989/ir31263095

Catégories
EN

When AI Meets Science: Research Diversity, Interdisciplinarity, Visibility, and Retractions across Disciplines in a Global Surge

Authors : Andrés F. Castro Torres, Joan Giner-Miguelez, Mercè Crosas

The extent to which Artificial Intelligence (AI) can trigger generalized paradigm shifts in science is unclear. Although some of these technologies have revolutionized data collection and analysis in specific scientific fields such as Chemistry, their overall impact depends on the scope of adoption and the ways scholars use them.

In this study, we document substantial differences in the timing and extent of AI adoption across countries and scientific domains from 1960 to 2015. After 2015, we find generalized exponential growth in AI adoption, with the number of AI-supported works multiplying by at least four across all domains. The transformative nature of this rapid growth is less apparent and points to multiple challenges should adoption trends persist.

According to our analyses, AI-supported research is confined to very few topics with strong ties to Computer Science and conventional statistical frameworks, suggesting limited transformational potential in epistemological terms. AI-supported works are also associated with an unwarranted citation premium and exhibit substantially higher retraction rates than non-AI-supported works across most fields.

Geographically, AI adoption displays pronounced heterogeneity at the country level, along with an acceleration in the relevance of middle-income countries in Asia, from China and beyond.

Thus, the transformative capacity of AI in science remains largely untapped, and its rapid adoption underlines challenges in research openness, transparency, reproducibility, and ethics from a global perspective. We discuss how best research practices could boost the benefits of AI adoption and highlight fields and geographies where these trends warrant closer scrutiny.

DOI : https://doi.org/10.48550/arXiv.2605.06033

Catégories
EN

AI And the Editors’ Ghost: Who Is the Writer Now?

Authors : David Clark, David Nicholas, Abdullah Abrizah, John Akeroyd, Jorge Revez, Blanca Rodríguez-Bravo, Marzena Swigon, Tatyana Polezhaeva, Anne Gere, Eti Herman

This an exploration of the use of AI in research and writing. It builds upon the ‘Harbingers’ project, an international and longitudinal study of early career researchers (ECRs) and scholarly communication.

In the fourth phase of the project, we returned to the theme of AI, in particular AI as ‘ghostwriter’. Our sources are transcripts of conversational, open-form interviews with over 60 ECRs from Britain, Malaysia, Poland, Portugal, Spain, Russia, and other countries.

For an initial analysis of the transcripts, we used Google NotebookLM. An overarching and thematic summary of the data was produced in minutes, that would otherwise have occupied our research team for weeks. The unprompted text, immediately plausible and coherent, was regarded by all national interviewers as impressive.

Here, using a relatively small, convenience sample, we compare the AI generated summaries both against our original data and those first impressions. We reflect upon our own experience of using AI and that of our interviewees.

This paper is about how we used AI as an experiment, our reaction to it, how that chimes, resonates, echoes the experiences of the ECRs. It is a calibration for our future data analysis.

URL : Learned Publishing – 2026 – Clark – AI And the Editors Ghost Who Is the Writer Now

DOI : https://doi.org/10.1002/leap.2051

Catégories
EN

Artificial intelligence in academic practices and policy discourses across ‘Big 5’ publishers

Authors :  Gergely Ferenc Lendvai, Aczél Petra

The present study investigates how the five largest academic publishers (Elsevier, Springer, Wiley, Taylor & Francis, and SAGE) are responding to the epistemic and procedural challenges posed by generative AI through formal policy frameworks.

Situated within ongoing debates about the boundaries of authorship and the governance of AI-generated content, our research aims to critically assess the discursive and regulatory contours of publishers’ authorship guidelines (PGs).

We employed a multi-method design that combines qualitative coding, semantic network analysis, and comparative matrix visualization to examine the official policy texts collected from each publisher’s website. Findings reveal a foundational consensus across all five publishers in prohibiting AI systems from being credited as authors and in mandating disclosure of AI usage.

However, beyond this shared baseline, marked divergences emerge in the scope, specificity, and normative framing of AI policies. Co-occurrence and semantic analyses underline the centrality of ‘authorship’, ‘ethics’, and ‘accountability’ in AI discourse. Structural similarity measures further reveal alignment among Wiley, Elsevier, and Taylor & Francis, with Springer as a clear outlier.

Our results point to an unsettled regulatory landscape where policies serve not only as instruments of governance but also as performative assertions of institutional identity and legitimacy.

Consequently, the fragmented field of PG highlights the need for harmonized, inclusive, and enforceable frameworks that recognize both the potential and risks of AI in scholarly communication.

URL : Artificial intelligence in academic practices and policy discourses across ‘Big 5’ publishers

DOI : https://doi.org/10.1093/reseval/rvag004

Catégories
EN

The scholarly communication attitudes and behaviours of Gen – Z researchers: a pathfinding study

Authors : David Nicholas, David Clark, Abdullah Abrizah, Jorge Revez, Blanca Rodrí guez-Bravo, Marzena Swigon, John Akeroyd

In preparation for a major study of Generation–Z early career researchers’ (ECRs) scholarly communications attitudes and practices we report on how different Gen-Z researchers included in our earlier studies of ECRs were.

It is a qualitative, pilot study that covered a convenience sample of around 30 Gen-Z ECRs from 8 countries and all subjects and compared to 120 of their older colleagues. Conversational, in-depth interviews lasting an hour or more were the main form of data collection.

An AI analysis, employing Claude AI, was used both to provide an initial analysis of the data and also assess the published literature on the topic. The findings were that there is enough evidence to suggest that there are enough differences between Gen-Z and their Millennial colleagues – even though all are ECRs – to merit further research.

Younger researchers in particular appear to be strategically adopting AI for efficiency and career advancement, while older researchers possess heightened awareness, and caution, regarding the philosophical and ethical consequences of technological transformation in scholarly communication.

URL : The scholarly communication attitudes and behaviours of Gen – Z researchers: a pathfinding study

DOI : https://doi.org/10.33774/coe-2026-s8b36

 

Catégories
FR

Pour une éthique de l’intelligence artificielle dans le domaine de l’évaluation de la recherche

Authors : Otmane Azeroual, Joachim Schöpfel

L’intelligence artificielle (IA) s’impose aujourd’hui dans de multiples secteurs, de la médecine à la logistique, en passant par la finance et l’éducation. Son intégration croissante dans les systèmes d’information sur la recherche (SI recherche) ouvre de nouvelles perspectives, mais soulève aussi des enjeux éthiques majeurs.

Cet article propose une réflexion sur le rôle de l’IA dans l’évaluation de la recherche, en mettant l’accent sur ses bénéfices, ses limites et la nécessité d’un cadre éthique rigoureux.

URL : Pour une éthique de l’intelligence artificielle dans le domaine de l’évaluation de la recherche

DOI : https://doi.org/10.4000/15gp8

Catégories
EN

A Cross-Disciplinary Analysis of AI Policies in Academic Peer Review

Authors : Zhongshi Wang, Mengyue Gong

Rapid advances of artificial intelligence (AI) have substantially impacted the field of academic publishing. This study examines AI integration in peer review by analysing policies from 439 high- and 363 middle-impact factor (IF) journals across disciplines. Using grounded theory, we identify patterns in AI policy adoption.

Results show 83% of high-IF journals have AI guidelines, with varying stringency across disciplines. Meanwhile, only 75% of middle-IF journals have AI guidelines. Science, technology, and medicine (STM) disciplines exhibit stricter regulations, while humanities and social sciences adopt more lenient approaches.

Key ethical concerns focus on confidentiality risks, accountability gaps, and AI’s inability to replicate critical human judgement. Publisher policies emphasise transparency, human oversight, and restricted AI usage for auxiliary tasks only, such as grammar checks or reviewer finding.

Disciplinary differences highlight the need for tailored guidelines that balance efficiency gains with research integrity. This study proposes collaborative frameworks for responsible AI integration. It focuses on accountability, transparency, and interdisciplinary policy development to address peer review challenges.

URL : A Cross-Disciplinary Analysis of AI Policies in Academic Peer Review

DOI : https://doi.org/10.1002/leap.2035