Assessing Dual Dimensions of Machine Learning Adoption in Libraries

Abstract

As a subset of artificial intelligence (AI), machine learning automatically enables a system to learn and improve from experience. This paper focuses on the two facets of the adoption of machine learning in libraries on library services. The study utilized a qualitative research approach and in so doing, the researcher adopted a systematic review of literature which helped in gathering data in line with the purpose of the study. Going by the reviewed literature, the first facet as identified, is that machine learning has the potential to enhancing access to information in libraries while the second facet, exposes the dangers associated with the adoption of machine learning in any library especially in the areas of technological growth and inclusivity in accessibility differences. In all, the emphasis is that libraries and librarians ought to adopt and lean on the associated gains of machine learning to harness its potentialities in libraries. The paper is of the opinion that libraries should come up with continual training and support to librarians and library users, libraries should partner stakeholders in digitization and related fields on comprehensive machine adoption in digital libraries and every other desirable information centres such as galleries and museums.