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Where there’s a will there’s a way: ChatGPT is used more for science in countries where it is prohibited

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Authors : Honglin Bao, Mengyi Sun, Misha Teplitskiy

Regulating AI has emerged as a key societal challenge, but which methods of regulation are effective is unclear. Here, we measure the effectiveness of restricting AI services geographically using the case of ChatGPT and science. OpenAI prohibits access to ChatGPT from several countries including China and Russia.

If the restrictions are effective, there should be minimal use of ChatGPT in prohibited countries. We measured use by developing a classifier based on prior work showing that early versions of ChatGPT overrepresented distinctive words like “delve.”

We trained the classifier on abstracts before and after ChatGPT “polishing” and validated it on held-out abstracts and those where authors self-declared to have used AI, where it substantially outperformed off-the-shelf LLM detectors GPTZero and ZeroGPT. Applying the classifier to preprints from Arxiv, BioRxiv, and MedRxiv reveals that ChatGPT was used in approximately 12.6% of preprints by August 2023 and use was 7.7% higher in countries without legal access.

Crucially, these patterns appeared before the first major legal LLM became widely available in China, the largest restricted-country preprint producer. ChatGPT use was associated with higher views and downloads, but not citations or journal placement.

Overall, restricting ChatGPT geographically has proven ineffective in science and possibly other domains, likely due to widespread workarounds.

URL : https://arxiv.org/abs/2406.11583

Virtual academic conferencing: a scoping review of 1984-2021 literature. Novel modalities vs. long standing challenges in scholarly communication

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Authors : Agnieszka Olechnicka, Adam Ploszaj, Ewa Zegler-Poleska

This study reviews the literature on virtual academic conferences, which have gained significant attention due to the COVID-19 pandemic. We conducted a scoping review, analyzing 147 documents available up to October 5th, 2021.

We categorized this literature, identified main themes, examined theoretical approaches, evaluated empirical findings, and synthesized the advantages and disadvantages of virtual academic conferences. We find that the existing literature on virtual academic conferences is mainly descriptive and lacks a solid theoretical framework for studying the phenomenon.

Despite the rapid growth of the literature documenting and discussing virtual conferencing induced by the pandemic, the understanding of the phenomenon is limited. We provide recommendations for future research on academic virtual conferences: their impact on research productivity, quality, and collaboration; relations to social, economic, and geopolitical inequalities in science; and their environmental aspects.

We stress the need for further research encompassing the development of a theoretical framework that will guide empirical studies.

URL : https://arxiv.org/abs/2406.11583

Open Science at the Generative AI Turn: An Exploratory Analysis of Challenges and Opportunities

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Authors : Mohammad Hosseini, Serge P.J.M. Horbach, Kristi L. Holmes, Tony Ross-Hellauer

Technology influences Open Science (OS) practices, because conducting science in transparent, accessible, and participatory ways requires tools/platforms for collaborative research and sharing results. Due to this direct relationship, characteristics of employed technologies directly impact OS objectives. Generative Artificial Intelligence (GenAI) models are increasingly used by researchers for tasks such as text refining, code generation/editing, reviewing literature, data curation/analysis.

GenAI promises substantial efficiency gains but is currently fraught with limitations that could negatively impact core OS values such as fairness, transparency and integrity, and harm various social actors. In this paper, we explore possible positive and negative impacts of GenAI on OS.

We use the taxonomy within the UNESCO Recommendation on Open Science to systematically explore the intersection of GenAI and OS. We conclude that using GenAI could advance key OS objectives by further broadening meaningful access to knowledge, enabling efficient use of infrastructure, improving engagement of societal actors, and enhancing dialogue among knowledge systems.

However, due to GenAI limitations, it could also compromise the integrity, equity, reproducibility, and reliability of research, while also having potential implications for the political economy of research and its infrastructure. Hence, sufficient checks, validation and critical assessments are essential when incorporating GenAI into research workflows.

URL : Open Science at the Generative AI Turn: An Exploratory Analysis of Challenges and Opportunities

DOI : https://doi.org/10.31235/osf.io/zns7g

Disciplinary Differences and Scholarly Literature: Discovery, Browsing, and Formats

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Authors : Chad E. Buckley, Rachel E. Scott, Anne Shelley, Cassie Thayer-Styes, Julie A Murphy

This study reports faculty experiences regarding the discovery of scholarly content, highlighting similarities and differences across a range of academic disciplines. The authors interviewed twenty-five faculty members at a public, high-research university in the Midwest to explore the intersections of discovery, browsing, and format from diverse disciplinary perspectives.

Although most participants rely on similar discovery tools such as library catalogs and databases and Google Scholar, their discovery techniques varied according to the discipline and type of research being done. Browsing is not a standard method for discovery, but it is still done selectively and strategically by some scholars.

Journal articles are the most important format across disciplines, but books, chapters, and conference proceedings are core for some scholars and should be considered when facilitating discovery. The findings detail several ways in which disciplinary and personal experiences shape scholars’ practices.

The authors discuss the perceived disconnect between browsability, discovery, and access of scholarly literature and explore solutions that make the library central to discovery and browsing.

URL : https://ir.library.illinoisstate.edu/fpml/196

Data Science and AI in Context: Summary and Insights

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Author : Alfred Spector

This paper explores how to deploy data science and data-driven AI, focusing on the broad collection of considerations beyond those of statistics and machine learning. Building on an analysis rubric introduced in a recent textbook by the author and three others, this paper summarizes some of the book’s key points and adds reflections on AI’s extraordinary growth and societal effects. The paper also discusses how to balance inevitable trade-offs and provides further thoughts on societal implications.

DOI : https://doi.org/10.1162/99608f92.cdebd845

Effects of Open Access. Literature study on empirical research 2010–2021

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Authors : David Hopf, Sarah Dellmann, Christian Hauschke, Marco Tullney

Open access — the free availability of scholarly publications — intuitively offers many benefits. At the same time, some academics, university administrators, publishers, and political decision-makers express reservations. Many empirical studies on the effects of open access have been published in the last decade. This report provides an overview of the state of research from 2010 to 2021.

The empirical results on the effects of open access help to determine the advantages and disadvantages of open access and serve as a knowledge base for academics, publishers, research funding and research performing institutions, and policy makers.

This overview of current findings can inform decisions about open access and publishing strategies. In addition, this report identifies aspects of the impact of open access that are potentially highly relevant but have not yet been sufficiently studied.

URL : Effects of Open Access. Literature study on empirical research 2010–2021

DOI : https://doi.org/10.34657/13648

Academic Integrity and Artificial Intelligence in Higher Education (HE) Contexts: A Rapid Scoping Review

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Authors : Beatriz Antonieta Moya, Sarah Elaine Eaton, Helen Pethrick, K. Alix Hayden, Robert Brennan, Jason Wiens, Brenda McDermott

Artificial Intelligence (AI) developments challenge higher education institutions’ teaching, learning, assessment, and research practices. To contribute timely and evidence-based recommendations for upholding academic integrity, we conducted a rapid scoping review focusing on what is known about academic integrity and AI in higher education. We followed the Updated Reviewer Manual for Scoping Reviews from the Joanna Briggs Institute (JBI) and the Preferred Reporting Items for Systematic reviews Meta-Analysis for Scoping Reviews (PRISMA-ScR) reporting standards.

Five databases were searched, and the eligibility criteria included higher education stakeholders of any age and gender engaged with AI in the context of academic integrity from 2007 through November 2022 and available in English. The search retrieved 2223 records, of which 14 publications with mixed methods, qualitative, quantitative, randomized controlled trials, and text and opinion studies met the inclusion criteria. The results showed bounded and unbounded ethical implications of AI.

Perspectives included: AI for cheating; AI as legitimate support; an equity, diversity, and inclusion lens into AI; and emerging recommendations to tackle AI implications in higher education. The evidence from the sources provides guidance that can inform educational stakeholders in decision-making processes for AI integration, in the analysis of misconduct cases involving AI, and in the exploration of AI as legitimate assistance. Likewise, this rapid scoping review signals key questions for future research, which we explore in our discussion.

URL : Academic Integrity and Artificial Intelligence in Higher Education (HE) Contexts: A Rapid Scoping Review

DOI : https://doi.org/10.55016/ojs/cpai.v7i3.78123