新兴的AI论文评审军备竞赛：学术出版中的对抗性共同进化

中文摘要 AI 辅助

生成式AI和智能体AI正在重塑科学研究的产生与评估。这些发展通常被分开研究，分别探讨AI如何产生研究以及AI如何评审研究。我们认为，这种分离忽略了学术出版中一个日益重要的特征：一方的变化会改变另一方的激励、约束和行为。我们使用一个包含六个相互关联动态的分类法综合了230篇学术出版物和机构记录：生产规模化、评估自动化、评估操纵、防御机制与政策应对、规避与副作用，以及长期生态系统反馈。文献显示出一个新兴的演进过程：更便宜、更快速的研究生产增加了评估压力，AI介导的评估变得更具可扩展性和可重复性，参与者可以利用评审者的规律性，机构则以技术保障和政策控制作为回应。这些回应反过来可能引发规避行为、重新分配错误和工作量，并塑造被未来研究和评估系统重复使用的学术记录。证据在规模化生产与评估、可复现的操纵以及机构回应方面最为有力，而政策后适应和工件层面的长期反馈则较少被直接观察到。这种系统视角将注意力从孤立的AI能力转向学术参与者和AI系统如何随时间相互适应。

英文摘要

Generative and agentic AI are reshaping both the production and evaluation of scientific research. These developments are often studied separately, as questions of how AI can produce research and how AI can review it. We argue that this separation misses an increasingly important feature of scholarly publishing: changes on one side alter the incentives, constraints, and behavior of the other. We synthesize 230 scholarly publications and institutional records using a taxonomy of six connected dynamics: production scaling, evaluation automation, evaluation manipulation, defense mechanisms and policy responses, evasion and side effects, and long-horizon ecosystem feedback. The literature shows an emerging progression in which cheaper and faster research production increases pressure on evaluation, AI-mediated evaluation becomes more scalable and repeatable, participants can exploit evaluator regularities, and institutions respond with technical safeguards and policy controls. These responses can in turn induce evasion, redistribute errors and workload, and shape the scholarly records reused by future research and evaluation systems. Evidence is strongest for production and evaluation at scale, reproducible manipulation, and institutional response, while post-policy adaptation and artifact-level long-horizon feedback remain less directly observed. This systems view shifts attention from isolated AI capabilities toward how scholarly actors and AI systems adapt to one another over time.

发表机构

• Virginia Tech（弗吉尼亚理工大学）
• University of Maryland（马里兰大学）
• Stony Brook University（石溪大学）
• MBZUAI（穆罕默德·本·扎耶德人工智能大学）

机构由 AI 辅助整理，请以论文原文为准。