Publication Type

Presentation

Version

publishedVersion

Publication Date

6-2025

Abstract

As AI-driven literature review tools become widespread, academic librarians must grapple with a fundamental question—should we ban these tools, selectively curate their use, or embrace them fully? This keynote explores the three competing schools of thought shaping AI’s role in undergraduate literature reviews.

The Restrict school argues that students who have not proven capable of writing quality literature review should be restricted from use of such tools. Much like handing a preschooler a calculator before they understand basic arithmetic will affect the learning of arithmetic, premature use of such tools has the potential to shortcut the research learning process. If students don’t first grasp how to evaluate sources, synthesize arguments, and conduct structured searches, AI tools risk fostering intellectual laziness rather than deeper engagement.

The Curate school takes a more nuanced stance—acknowledging that not all AI tools are the same. There is a fundamental difference between AI tools that help students find relevant literature—such as ResearchRabbit and Connected Papers (which use citation searching) or semantic search engines (which can be seen as souped-up keyword-based discovery)—and AI tools that generate direct answers with citations via retrieval-augmented generation (RAG). The former encourages students to explore and engage with literature, while the latter risks short-circuiting the critical reading and synthesis process by providing pre-packaged conclusions. Librarians should guide students toward AI tools that enhance discovery without bypassing the intellectual rigor of evaluating and synthesizing sources themselves.

The Embrace school argues that resisting AI is futile. Just as students had to learn to navigate Google and Wikipedia in past decades, they now need to master AI research tools because these technologies are becoming standard in academic and professional environments. Rather than restrict access, educators should teach students how to critically engage with AI-generated content and use these tools effectively. However, this approach can be more challenging for both instructors and students, as it requires the simultaneous development of traditional research skills and proficiency with AI tools, much like learning to ride a bike and juggle at the same time.

This keynote will critically examine each perspective, offering practical strategies for librarians to help students develop both traditional and AI-augmented research skills while maintaining academic integrity and rigor.

Keywords

AI in education, academic librarianship, literature review tools, undergraduate research, research instruction, educational technology, critical thinking, semantic search, retrieval-augmented generation, academic integrity

Discipline

Artificial Intelligence and Robotics | Information Literacy | Library and Information Science

Publication

Business Librarians Association (BLA) Summer Conference, University of Stirling, 2025 June 25-27

First Page

1

Last Page

57

City or Country

Scotland

Embargo Period

7-1-2025

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