Below is a structured guide to help academic librarians expand their roles in supporting artificial intelligence (AI) initiatives and services. This framework focuses on text and data mining (TDM), advanced query mediation, and AI-enhanced discovery systems, among other key responsibilities.
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Key Takeaways:
Implementing the strategies outlined in this guide can help librarians become indispensable partners in TDM initiatives, advancing individual research projects and the broader mission of the academic institution.
As artificial intelligence (AI) becomes increasingly integrated into academic libraries, the principles that have governed their operations for generations face new challenges. Advanced technologies bring many benefits, from more efficient cataloging and retrieval systems to personalized recommendations that match readers with the resources most relevant to their needs. However, these capabilities often require massive amounts of user data, sparking critical conversations about privacy, consent, and potential misuse. The tension between maximizing AI's benefits and honoring core library values requires thoughtful reflection and urgent and proactive measures to address ethical dilemmas and maintain user trust.
