Integrating AI literacy into library and information science education and practice: a human-centered approach

Abstract

Purpose This opinion essay aims to propose a human-centered, developmental framework for integrating artificial intelligence (AI) literacy into Library and Information Science (LIS) education and practice. It addresses the growing need for structured AI competency among LIS students and professionals, particularly in regions facing systemic educational and infrastructural challenges. Design/methodology/approach This paper draws on empirical findings from two interconnected studies led and co-led by the author: one explores the AI literacy (AiL) of LIS students across 11 countries in South Asia, Africa and the Middle East, while the other examines the AiL of LIS professionals in 6 countries within South Asia and the Middle East. These insights are synthesized with global policy guidance, existing AiL frameworks and practical teaching models to propose a four-stage human-centered AiL framework consisting of Foundational, Operational, Critical and Transformational domains. Findings The findings from the studies, along with related literature highlight widespread use of generative AI tools for basic academic and professional tasks, but limited understanding of ethical, technical and critical dimensions. Structural barriers – including inadequate curricula, unprepared faculty/professional and limited institutional infrastructure – further hinder effective AiL. The proposed human-centered AiL framework offers a practical roadmap for designing scalable, inclusive and reflective AiL strategies in LIS education and practice. Originality/value This essay presents a context-specific model grounded in underexplored regions and real-world professional environments. While conceptually comprehensive, the framework requires further empirical validation and adaptation based on institutional resources and country/regional educational policies.

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