Mishra Tanisha, Sutanto Edward, Rossanti Rini, Pant Nayana, Ashraf Anum, Raut Akshay, Uwabareze Germaine, Oluwatomiwa Ajayi, Zeeshan Bushra
Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
Nuffield Department of Medicine, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, OX3 7LG, UK.
Sci Rep. 2024 Dec 30;14(1):31672. doi: 10.1038/s41598-024-81370-6.
With breakthroughs in Natural Language Processing and Artificial Intelligence (AI), the usage of Large Language Models (LLMs) in academic research has increased tremendously. Models such as Generative Pre-trained Transformer (GPT) are used by researchers in literature review, abstract screening, and manuscript drafting. However, these models also present the attendant challenge of providing ethically questionable scientific information. Our study provides a snapshot of global researchers' perception of current trends and future impacts of LLMs in research. Using a cross-sectional design, we surveyed 226 medical and paramedical researchers from 59 countries across 65 specialties, trained in the Global Clinical Scholars' Research Training certificate program of Harvard Medical School between 2020 and 2024. Majority (57.5%) of these participants practiced in an academic setting with a median of 7 (2,18) PubMed Indexed published articles. 198 respondents (87.6%) were aware of LLMs and those who were aware had higher number of publications (p < 0.001). 18.7% of the respondents who were aware (n = 37) had previously used LLMs in publications especially for grammatical errors and formatting (64.9%); however, most (40.5%) did not acknowledge its use in their papers. 50.8% of aware respondents (n = 95) predicted an overall positive future impact of LLMs while 32.6% were unsure of its scope. 52% of aware respondents (n = 102) believed that LLMs would have a major impact in areas such as grammatical errors and formatting (66.3%), revision and editing (57.2%), writing (57.2%) and literature review (54.2%). 58.1% of aware respondents were opined that journals should allow for use of AI in research and 78.3% believed that regulations should be put in place to avoid its abuse. Seeing the perception of researchers towards LLMs and the significant association between awareness of LLMs and number of published works, we emphasize the importance of developing comprehensive guidelines and ethical framework to govern the use of AI in academic research and address the current challenges.
随着自然语言处理和人工智能（AI）领域的突破，大语言模型（LLMs）在学术研究中的应用急剧增加。诸如生成式预训练变换器（GPT）等模型被研究人员用于文献综述、摘要筛选和论文起草。然而，这些模型也带来了提供道德上有问题的科学信息这一随之而来的挑战。我们的研究提供了全球研究人员对大语言模型在研究中的当前趋势和未来影响的看法的一个概况。采用横断面设计，我们调查了来自59个国家65个专业的226名医学和准医学研究人员，他们于2020年至2024年期间参加了哈佛医学院全球临床学者研究培训证书项目。这些参与者中的大多数（57.5%）在学术环境中工作，发表的被PubMed索引的文章中位数为7篇（2，18）。198名受访者（87.6%）知晓大语言模型，且知晓者发表的文章数量更多（p < 0.001）。18.7%知晓的受访者（n = 37）此前在发表物中使用过大语言模型，特别是用于检查语法错误和格式（64.9%）；然而，大多数（40.5%）并未在其论文中承认使用过。50.8%知晓的受访者（n = 95）预测大语言模型未来总体上会产生积极影响，而32.6%不确定其影响范围。52%知晓的受访者（n = 102）认为大语言模型将在语法错误和格式（66.3%）、修订和编辑（57.2%）、写作（57.2%）和文献综述（54.2%）等领域产生重大影响。58.1%知晓的受访者认为期刊应允许在研究中使用人工智能，78.3%认为应制定相关规定以避免其被滥用。鉴于研究人员对大语言模型的看法以及大语言模型知晓度与已发表作品数量之间的显著关联，我们强调制定全面的指南和道德框架以规范人工智能在学术研究中的使用并应对当前挑战的重要性。
