AI 中文总结
研究探讨生成式人工智能在科研中的利弊及治理问题，借助圆桌会议和文献梳理分歧，指出私人与社会回报差异的机制，进而提出围绕四个原则的负责任人工智能研究框架，以平衡风险与成果。
AI 中文摘要
本文探讨了生成式人工智能对科学研究的益处与快速采用所带来的未解决治理问题之间的矛盾。借助在人工智能促进科学与创新研讨会上举行的学术圆桌会议以及快速增长的实证文献，梳理了研究界在研究过程的四个阶段（资助、研究任务、出版与同行评审、使用与推广）的分歧。人工智能的生产力、增强作用和民主化效应的实证依据有所加强，但细分生产力时情况不同。私人回报与社会回报的差异通过信息不对称、对共享知识库的负外部性、研究能力的消耗这三种机制产生，每种都需要不同治理手段。我们提出负责任的人工智能研究（RRAI），它围绕研究系统不同层面运作的四个原则展开，基于现有制度框架构建，旨在在解决系统性风险的同时保留人工智能的生产力提升成果。
英文摘要
This paper examines the tension between the benefits of generative artificial intelligence (AI) for scientific research and the unresolved governance questions that accompany its rapid adoption. Drawing on an academic roundtable held at the AI for Science and Innovation Workshop (Scuola IMT Alti Studi Lucca, April 2026) and on a fast-expanding empirical literature, it maps the disagreement within the research community across four stages of the research process: funding, research tasks, publication and peer review, and use and uptake. The empirical case for AI's productivity, augmentation, and democratization effects has strengthened. The picture changes once productivity is disaggregated: AI-assisted work shows measurable gains in publication volume and citation share, while the evidence on novelty, disruption, and breakthrough output remains ambiguous or negative. We argue that the divergence between private and social returns arises through three analytically distinct mechanisms, namely information asymmetry, negative externalities on a shared knowledge base, and depletion of research capacity, and that each calls for a different governance instrument. We propose Responsible Research with AI (RRAI), an extension of the Responsible Research and Innovation tradition organized around four principles that operate at different levels of the research system: disclosure, differentiation, narrative, and proportionality. RRAI builds on existing institutional scaffolding, including the EU AI Act, UNESCO, and the OECD, and aims to preserve AI's productivity gains while addressing systemic risks that individual researchers can neither observe nor manage on their own.
