Artificial intelligence behind the scenes: PubMed's Best Match algorithm.

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 algor...

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Publicado en:Journal of the Medical Library Association Vol. 110; no. 1; pp. 15 - 23
Autores principales: Kiester, Lucy, Turp, Clara
Formato: pictorial Journal Article
Publicado: University of Pittsburgh, University Library System Jan2022
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Artificial intelligence behind the scenes: PubMed's Best Match algorithm.
      aug:
        au:
          Kiester, Lucy
          Turp, Clara
        affil: Liaison Librarian, McGill University Library, Montreal, Quebec, Canada
      sug:
        subj:
          Artificial Intelligence
          PubMed
          Algorithms
          Medical Informatics
          Information Retrieval
          Web Search Engines
          Data Mining
          Decision Support Systems, Clinical
          Automation
          User-Computer Interface
          Information Seeking Behavior
          Decision Making, Clinical
      ab: 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?
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      doctype:
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        Journal Article
      ougenre: Article
    language: English
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