Confirming the Query Search Method: Balancing AI Advancements in Reference Services
DOI:
https://doi.org/10.21900/j.alise.2024.1626Keywords:
artificial intelligence (AI), pedagogy, praxis, query search method (QSM), referenceAbstract
Although artificial intelligence (AI) has quickly become a tool that offers quick, simplistic answers to reference questions (Chen, 2023), in this paper, we interrogate AI’s ability to consider the human-to-human interpersonal nuances that occur and are vital to answering queries. We ask: what is most essential for reference services - human knowledge sharing or the machine’s artificial intelligence? AI, as a mechanistic language model, cannot discern the subtleties of humanity’s questions; AI itself admits that librarians are more efficient at answering reference queries from a humanistic approach and lens (Yang & Mason, 2023). This paper is the second part of our introduction to our methodology for reference services, the Query Search Method (QSM). We present conceptual substantiation that, when enacted, the QSM can incorporate AI as an addition to the librarian’s toolbox for honoring patrons’ ways of knowing that, through the sententiousness of the human experience, invariably seek knowledge beyond “the machine.”
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