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Artificial Intelligence in Subject-Specific Library Work: Perspectives, Trends, and Opportunities

Quoi:
Posters
Quand:
3:30 PM, Mardi 26 Avr 2022 EDT (55 minutes)
Où:
  Session virtuelle
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Comment:

Erica Friesen, Research and Instruction Librarian (Law) and Online Learning Specialist, Queen's University
Angélique Roy, Health Sciences Librarian, Queen's University
Hannah Tanna, Research and Instruction Librarian (Humanities & Social Sciences), Queen's University
 

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Our project’s goal is to conduct a review of the contexts in which artificial intelligence (AI) is being discussed by librarians in different subject specialties such as law, health sciences, and the humanities. The general implications of AI for libraries are much discussed in LIS literature. These include, for example, implications for instruction (e.g. teaching algorithmic literacy), patron services (e.g. AI-driven library chatbots), and collections (e.g. the datafication of the library collection to facilitate AI research). But while this discussion is taking place at library-wide level, there are also important implications for subject specialists due to the specific and varied uses of AI in different professions and areas of academic study. As subject librarians, we often experience tunnel vision that narrows our focus to subject-specific literature without considering that similar or otherwise relevant work may be done in other subject areas. By compiling an overview of how these contexts differ between library subspecialties, we hope this collaborative project will shed light on these similarities and differences and promote greater synergies between those working in disparate fields. Some questions we will explore include: - Do certain library subject specializations place greater emphasis on integrating AI into their practices? For example, is AI a greater topic of interest in professional specialties like law and business, where students are more likely to encounter these technologies in a professional capacity? - Are certain themes more prominent in some fields than others, and why might this be? - What similarities and differences exist regarding the ways in which the same AI theme (e.g. algorithmic literacy) is discussed by librarians in different subject areas? - Are there any emerging trends and opportunities that we can identify between certain types of libraries or specialties? - How can we leverage these findings to increase collaboration across disciplines? We are not limiting this project to academic library literature in order to also encompass the work being done by those in professional libraries (e.g. law firm libraries, hospital libraries).

 

Twitter hashtag: #CULibraryForum  

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