International Journal of Science, Engineering and TechnologyAuthors: Haridas Karmakar
Abstract: Artificial intelligence (AI) and machine learning (ML) are increasingly shaping the way libraries organize knowledge, describe resources, and interact with users. In academic libraries, these technologies promise faster classification, automated metadata enrichment, improved discovery, and more responsive user services. Yet their adoption also raises serious questions about bias, transparency, privacy, professional accountability, and growing dependence on vendor-controlled systems. This conceptual paper examines the application of AI and ML in three core areas of library practice: classification, cataloguing, and user services, with particular attention to the Indian academic library context. Drawing on library and information science literature, together with policy and ethical guidance, the paper argues that AI in libraries should be understood not as a neutral automation tool, but as a sociotechnical intervention that affects representation, access, and trust. The paper proposes a trustworthy sociotechnical framework based on six dimensions: task-risk alignment, data and metadata stewardship, human accountability, transparency and contestability, user rights and inclusion, and organizational readiness. It concludes that AI can strengthen library work only when it remains aligned with professional judgment, user welfare, and the public mission of librarianship.
DOI: https://doi.org/10.5281/zenodo.18922501
