GenAI正快速进入科学领域，但其长期影响仍不明朗。
Generative AI in Science: Applications, Challenges, and Emerging Questions
- 通过文献分析法筛选高影响力论文，系统梳理GenAI在科研中的应用
- 发现GenAI在科学写作、医疗实践和教育中已被广泛采用
- 揭示其治理与长期影响的不确定性，适合关注AI与科学交叉的研究者
本文考察生成式人工智能（GenAI）对科学实践的影响，基于对精选文献的定性综述，探讨其应用、优势与挑战。研究利用OpenAlex出版数据库，通过布尔检索识别与GenAI（含大语言模型和ChatGPT）相关的科学文献，共筛选出39篇高被引论文与评论并进行定性编码。结果按GenAI在科学、科学写作、医疗实践及教育训练中的应用分类。分析表明，尽管GenAI在科学研究与实践中迅速普及，但其长期影响尚不明确，使用与治理方面仍存在持续不确定性。研究为GenAI在科学领域的角色提供了初步洞察，并指出了未来研究的关键问题。
原文摘要 · Abstract (English)
This paper examines the impact of Generative Artificial Intelligence (GenAI) on scientific practices, conducting a qualitative review of selected literature to explore its applications, benefits, and challenges. The review draws on the OpenAlex publication database, using a Boolean search approach to identify scientific literature related to GenAI (including large language models and ChatGPT). Thirty-nine highly cited papers and commentaries are reviewed and qualitatively coded. Results are categorized by GenAI applications in science, scientific writing, medical practice, and education and training. The analysis finds that while there is a rapid adoption of GenAI in science and science practice, its long-term implications remain unclear, with ongoing uncertainties about its use and governance. The study provides early insights into GenAI's growing role in science and identifies questions for future research in this evolving field.
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