A growing literature documents that generative artificial intelligence (GenAI) is changing scientific writing, yet most studies focus on absolute changes in vocabulary or readability. An important question remains unanswered: Does GenAI use lead to systematic convergence, or a narrowing of stylistic gaps relative to the dominant form of scientific English? Unlike absolute changes, convergence signals whether language-related publication barriers are declining and suggests broader implications for participation and competition in global science. This study directly addresses this question using 5.65 million English-language scientific articles published from 2021 to 2024 and indexed in Scopus. We measure linguistic similarity to a U.S. benchmark corpus using SciBERT text embeddings, and estimate dynamic changes using an event-study difference-in-differences design with repeated cross-sections centered on the late-2022 release of ChatGPT. We find that GenAI-assisted publications from non-English-speaking countries exhibit statistically significant and increasing convergence toward U.S. scientific English, relative to non-GenAI-assisted publications from these countries. This effect is strongest for domestic author teams from countries more linguistically distant from English and for articles published in lower-impact journals -- precisely the contexts where language barriers have historically been most consequential. The results suggest that GenAI tools are reducing language-related barriers in scientific publications. Whether this represents genuine inclusion or a deepening dependence on a single linguistic standard remains an open question.

翻译：越来越多的文献表明，生成式人工智能（GenAI）正在改变科学写作，但大多数研究仅关注词汇或可读性的绝对变化。一个重要问题仍未得到解答：GenAI的使用是否会导致系统性趋同，即科学写作风格相对于主流科学英语形式的差距缩小？与绝对变化不同，趋同现象能够揭示语言相关的发表障碍是否正在减少，并暗示全球科学参与和竞争格局的更广泛影响。本研究利用Scopus收录的2021年至2024年间发表的565万篇英文科学论文，直接探讨了这一问题。我们使用SciBERT文本嵌入技术测量文本与美国基准语料库的语言相似度，并采用以2022年末ChatGPT发布为中心事件、基于重复横截面数据的事件研究双重差分设计来估计动态变化。研究发现，与非英语国家未使用GenAI辅助的出版物相比，这些国家使用GenAI辅助的出版物在统计上显著且日益趋近美式科学英语。这种效应在英语语言距离较远国家的本土作者团队以及较低影响力期刊上发表的文章中最为明显——这些正是历史上语言障碍影响最为深远的场景。结果表明，GenAI工具正在降低科学出版物中的语言相关障碍。这究竟代表了真正的包容性提升，还是意味着对单一语言标准的依赖加深，仍是一个有待探讨的问题。