AI Chatbots and Subject Cataloging: A Performance Test

Libraries show an increasing interest in incorporating AI tools into their workflows, particularlyeasily accessible and free-to-use chatbots. However, empirical evidence is limited regarding theeffectiveness of these tools to perform traditionally time-consuming subject cataloging tasks. In thisstud...

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Bibliographic Details
Published inLibrary resources & technical services Vol. 69; no. 2
Main Authors Dobreski, Brian, Hastings, Christopher
Format Journal Article
LanguageEnglish
Published Chicago American Library Association 01.04.2025
Subjects
Artificial intelligence
Chatbots
Classification
Effectiveness
Performance tests
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ISSN0024-2527
2159-9610
DOI10.5860/lrts.69n2.8440

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Summary:Libraries show an increasing interest in incorporating AI tools into their workflows, particularlyeasily accessible and free-to-use chatbots. However, empirical evidence is limited regarding theeffectiveness of these tools to perform traditionally time-consuming subject cataloging tasks. In thisstudy, researchers sought to assess the performance of AI tools in performing basic subject headingand classification number assignment. Using a well-established instructional cataloging text as abasis, researchers developed and administered a test designed to evaluate the effectiveness of three chatbots (ChatGPT, Gemini, Copilot) in assigning Dewey Decimal Classification, Library of Congress Classification, and Library of Congress Subject Heading terms and numbers. The quantity and quality of errors in chatbot responses were analyzed.
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ISSN:0024-2527
2159-9610
DOI:10.5860/lrts.69n2.8440