ICLR 2025首次实测AI辅助审稿，发现工具提升效率但引发责任争议。
What happens when reviewers receive AI feedback in their reviews?
- 在ICLR 2025审稿中部署AI反馈工具，生成后置审稿建议。
- 多数审稿人认可工具帮助，但担心削弱个人责任与判断独立性。
- 研究为未来设计可信赖的AI辅助审稿系统提供关键实践依据。
人工智能正在重塑学术研究，但在同行评审中的角色仍存在分歧。支持者认为其可减轻审稿负担、提升质量，反对者则担忧公平性、问责制和信任问题。在ICLR 2025中，官方部署了AI反馈工具，在审稿后向审稿人提供改进建议。我们通过问卷调查与访谈，研究了审稿人如何使用该工具及其对可用性和影响的感知。研究揭示了在同行评审中引入AI带来的机遇与张力。本文首次提供了在真实评审流程中使用AI工具的实证证据，记录了高压力环境下审稿人对AI生成反馈的响应情况。同时，研究提出了增强评审质量的同时保障人类专家能力、自主权与责任的设计建议。
原文摘要 · Abstract (English)
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.
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