AI is reshaping academic research, yet its role in peer review remains polarising and contentious. Advocates see its potential to reduce reviewer burden and improve quality, while critics warn of risks to fairness, accountability, and trust. At ICLR 2025, an official AI feedback tool was deployed to provide reviewers with post-review suggestions. We studied this deployment through surveys and interviews, investigating how reviewers engaged with the tool and perceived its usability and impact. Our findings surface both opportunities and tensions when AI augments in peer review. This work contributes the first empirical evidence of such an AI tool in a live review process, documenting how reviewers respond to AI-generated feedback in a high-stakes review context. We further offer design implications for AI-assisted reviewing that aim to enhance quality while safeguarding human expertise, agency, and responsibility.

翻译：人工智能正在重塑学术研究，但其在同行评审中的作用仍存在两极分化和争议。支持者认为其具有减轻审稿负担、提升质量的潜力，而批评者则警告其对公平性、问责制与信任体系构成风险。在ICLR 2025会议上，官方部署了一款AI反馈工具，为审稿人提供评审后的修改建议。我们通过问卷调查与深度访谈研究了该工具的部署情况，探究审稿人如何使用该工具，以及对其可用性与影响的认知。研究发现揭示了AI增强同行评审过程中的机遇与矛盾。本研究首次为实时评审流程中此类AI工具的应用提供了实证证据，记录了在高风险评审情境下审稿人对AI生成反馈的响应机制。我们进一步提出了AI辅助评审的设计启示，旨在提升评审质量的同时，保障人类专家的专业判断力、自主权与责任归属。