Application of Artificial Intelligence and Machine Learning in Libraries: A Systematic Review
arXiv:2112.04573v2 Announce Type: replace-cross Abstract: As the concept and implementation of cutting-edge technologies like artificial intelligence and machine learning has become relevant, academics, researchers and information professionals involve research in this area. The objective of this systematic literature review is to provide a synthesis of empirical studies exploring application of artificial intelligence and machine learning in libraries. To achieve the objectives of the study, a systematic literature review was conducted based on the original guidelines proposed by Kitchenham e
The proliferation of AI/ML technologies has reached a maturity where their systematic application across diverse sectors, including information management, warrants formal review and synthesis.
This systematic review highlights the increasing penetration of AI and machine learning into traditional knowledge sectors, suggesting a transformation in how information is organized, accessed, and managed.
The systematic review identifies and consolidates various applications of AI/ML in libraries, shifting the perception of these technologies from experimental to practical tools in information science.
- · AI/ML developers
- · Information science researchers
- · Libraries adopting AI tools
- · Patrons benefiting from improved library services
- · Traditional manual information processing methods
- · Libraries slow to adopt new technologies
Libraries will increasingly integrate AI and ML tools for tasks like cataloging, recommendation systems, and user interaction.
The role of librarians will evolve, focusing more on managing AI systems and training users rather than solely manual information handling.
This widespread integration could lead to new standards and ethical considerations for AI use in public information access and intellectual property management.
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