How Heavily Are PhD Students Offloading Their Scientific Writing to AI? Evidence from US STEM PhD Dissertations
NBER Working Papers · 2026 · Daniel P. Gross、Dror Shvadron、Hansen Zhang
中文摘要
大语言模型正迅速扩散至科学领域，引发了人们的担忧：将研究写作委托给AI，可能削弱科学训练本应培养的专业技能。我们测量了2019年至2026年间近乎全体的美国STEM博士毕业生学位论文中的AI生成写作，并将毕业生与其后续就业相链接。2023年之前不存在AI写作，而在2026年提交的学位论文中有29%存在AI写作，且增长迅速。来自非英语国家的学生以及排名较低项目的学生中，这种使用更为常见。在同一项目和同届的毕业生中，学位论文含AI写作者更不可能进入学术研究职业，更可能进入非终身教职轨道岗位或产业界，且这一模式在美国本土学生中最为明显。在AI可能提高研究生产率的同时，它似乎也在取代一部分用于培养科学专业技能的潜在重要工作。
Abstract
Large language models are diffusing rapidly into science, raising concerns that delegating research writing to AI may undermine the development of expertise that scientific training is supposed to build. We measure AI-generated writing in the dissertations of a near-census of US STEM PhD graduates from 2019 to 2026 and link graduates to their subsequent employment. AI writing is absent before 2023, present in 29% of dissertations filed in 2026, and rapidly growing. Use is more common among students from non-English-speaking countries and at lower-ranked programs. Among graduates in the same program and cohort, those whose dissertations contain AI writing are less likely to enter academic research careers and more likely to enter non-tenure-track roles or industry, with this pattern strongest among US-origin students. At the same time as AI may increase research productivity, it thus appears to also be displacing a potentially important portion of the work through which scientific expertise is developed.