让同行评审适应未来:同行评审中的数字干扰与信任

IF 2.2 3区 管理学 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE Learned Publishing Pub Date : 2024-01-15 DOI:10.1002/leap.1594
Harini Calamur, Roohi Ghosh
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引用次数: 0

摘要

仙人掌通信(CACTUS)在2022年同行评议周期间进行的全球调查收集了685名参与者对研究诚信和同行评议的见解。调查参与者强调了同行评审在发现各种问题(包括剽窃和有问题的研究实践)方面的重要性。针对诚信问题采取的行动各不相同,一些参与者向同事寻求指导或通知期刊编辑。人工智能剽窃检测工具扫描补充了人类的努力,提供了一个额外的审查层。数字创新的增加允许灵活的审稿形式、国际合作和提高审稿过程的透明度。将人工智能融入同行评议有可能提高效率和客观性,但也会引发对偏见和透明度的担忧。指导方针、偏见缓解措施、问责机制和持续培训对于在同行评议中负责任地使用人工智能至关重要。鼓励同行评议系统接受创新和合乎道德的人工智能对于适应不断变化的动态,同时坚持研究诚信的核心原则至关重要。
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Adapting peer review for the future: Digital disruptions and trust in peer review

  • Academia is undergoing transformation with rapid technological advancements, global collaboration, and the rise of AI.
  • Maintaining research integrity is paramount in the face of new challenges and opportunities.
  • The peer review process, vital for research integrity, is strained due to the high volume of academic papers.
  • Cactus Communication's (CACTUS) global survey during Peer Review Week 2022 gathered insights from 685 participants on research integrity and peer review.
  • Survey participants emphasized the importance of peer review in detecting various issues, including plagiarism and questionable research practices.
  • Actions taken in response to integrity concerns varied, with some participants seeking guidance from colleagues or informing journal editors.
  • Digital innovations, especially AI-driven tools, promise to revolutionize peer review processes, from manuscript screening to reviewer selection and evaluation.
  • AI tools like Chat GPT can aid authors in improving writing quality and assist reviewers in generating detailed feedback.
  • Concerns about data privacy and the need for a balance between human expertise and AI assistance are raised in the context of peer review.
  • AI plagiarism detection tool scan complement human efforts, providing an additional layer of scrutiny.
  • Increased digital innovation allows for flexible review formats, international collaboration, and heightened transparency in the review process.
  • The integration of AI into peer review holds the potential to enhance efficiency and objectivity but raises concerns about bias and transparency.
  • Guidelines, bias mitigation measures, accountability mechanisms, and ongoing training are essential for the responsible use of AI in peer review.
  • Encouraging peer review systems to embrace innovation and ethical AI is crucial for adapting to changing dynamics while upholding core principles of research integrity.
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来源期刊
Learned Publishing
Learned Publishing INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
4.40
自引率
17.90%
发文量
72
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