The dominance of English in global science has long created significant barriers for non-native speakers. The recent emergence of generative artificial intelligence (GenAI) dramatically reduces drafting and revision costs, but, simultaneously, raises a critical question: how is the technology being adopted by the global scientific community, and is it mitigating existing inequities? This study provides first large-scale empirical evidence by analyzing over two million full-text biomedical publications from PubMed Central from 2021 to 2024, estimating the fraction of AI-generated content using a distribution-based framework. We observe a significant post-ChatGPT surge in AI-assisted writing, with adoption growing fastest in contexts where language barriers are most pronounced: approximately 400% in non-English-speaking countries compared to 183% in English-speaking countries. This adoption is highest among less-established scientists, including those with fewer publications and citations, as well as those in early career stages at lower-ranked institutions. Prior AI research experience also predicted higher adoption. Finally, increased AI usage was associated with a modest increase in productivity, narrowing the publication gap between scientists from English-speaking and non-English-speaking countries with higher levels of AI adoption. These findings provide large-scale evidence that generative AI is being adopted unevenly, reflecting existing structural disparities while also offering a potential opportunity to mitigate long-standing linguistic inequalities.

翻译：英语在全球科学领域的主导地位长期以来为非母语研究者设置了显著障碍。近期生成式人工智能（GenAI）的出现大幅降低了论文起草与修改的成本，但同时也引发了一个关键问题：全球科学界如何采纳这项技术？它是否正在缓解现有的不平等现象？本研究通过分析PubMed Central数据库中2021年至2024年间超过两百万篇生物医学领域全文出版物，采用基于分布的框架估算AI生成内容的比例，首次提供了大规模实证证据。我们观察到ChatGPT发布后AI辅助写作出现显著激增，在语言障碍最突出的情境中采纳增速最快：非英语国家约增长400%，而英语国家为183%。这种采纳在资历较浅的科学家中最为普遍，包括发表成果较少、引用量较低的研究者，以及任职于较低排名机构的早期职业学者。先前的人工智能研究经验同样预示着更高的采纳率。最后，AI使用率的提升与生产力的适度增长相关，缩小了高AI采纳水平的英语国家与非英语国家科学家之间的发表差距。这些发现提供了大规模证据，表明生成式人工智能的采纳存在不均衡性，既反映了现有结构性差异，也为缓解长期存在的语言不平等提供了潜在机遇。