文章基本信息

标题：Artificial intelligence behind the scenes: PubMed's Best Match algorithm
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作者：Lucy Kiester ; Clara Turp
期刊名称：Journal of the Medical Library Association
印刷版ISSN：1536-5050
出版年度：2022
卷号：110
期号：1
页码：15-22
DOI：10.5195/jmla.2022.1236
语种：English
出版社：Medical Library Association
摘要：This article focuses on PubMed's Best Match sorting algorithm, presenting a simplified explanation of how it operates and highlighting how artificial intelligence affects search results in ways that are not seen by users. We further discuss user search behaviors and the ethical implications of algorithms, specifically for health care practitioners. PubMed recently began using artificial intelligence to improve the sorting of search results using a Best Match option. In 2020, PubMed deployed this algorithm as the default search method, necessitating serious discussion around the ethics of this and similar algorithms, as users do not always know when an algorithm uses artificial intelligence, what artificial intelligence is, and how it may impact their everyday tasks. These implications resonate strongly in health care, in which the speed and relevancy of search results is crucial but does not negate the importance of a lack of bias in how those search results are selected or presented to the user. As a health care provider will not often venture past the first few results in search of a clinical decision, will Best Match help them find the answers they need more quickly? Or will the algorithm bias their results, leading to the potential suppression of more recent or relevant results?
关键词：enPubMedBest Matchinformation systemsartificial intelligenceinformation-seeking behavior