技术辅助研究评估:算法偏差和透明度问题

Mike Thelwall, Kayvan Kousha
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引用次数: 0

摘要

技术有时被用于支持学术研究的评估,其形式是自动生成的文献计量学,供审稿人在评估期间参考,或者通过取代部分或全部的人类判断。随着人工智能(AI)的发展,利用技术以新的方式协助研究评估过程的范围越来越大。由于透明度和公平性在研究评估中被广泛认为是重要的,而人工智能引入了新的问题,本综述探讨了它们的含义。本文回顾并简要总结了一般意义上的透明度和公平性问题,以及它们为各种类型的技术辅助研究评估(TARA)提出的问题。虽然TARA在透明度和偏见方面可能存在不同程度的问题,但在大多数情况下,尚不清楚它是否会加剧同行评议中固有的透明度和偏见问题。原创性/价值这是第一个专注于算法偏见和技术辅助研究评估透明度问题的分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Technology assisted research assessment: algorithmic bias and transparency issues
Purpose Technology is sometimes used to support assessments of academic research in the form of automatically generated bibliometrics for reviewers to consult during their evaluations or by replacing some or all human judgements. With artificial intelligence (AI), there is increasing scope to use technology to assist research assessment processes in new ways. Since transparency and fairness are widely considered important for research assessment and AI introduces new issues, this review investigates their implications. Design/methodology/approach This article reviews and briefly summarises transparency and fairness concerns in general terms and through the issues that they raise for various types of Technology Assisted Research Assessment (TARA). Findings Whilst TARA can have varying levels of problems with both transparency and bias, in most contexts it is unclear whether it worsens the transparency and bias problems that are inherent in peer review. Originality/value This is the first analysis that focuses on algorithmic bias and transparency issues for technology assisted research assessment.
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来源期刊
Aslib Proceedings
Aslib Proceedings 工程技术-计算机:信息系统
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