Augmented intelligence technology. The ethical and practical problems of its implementation in libraries

Why do people not attend public library programs in the current digital age? A mix method study in Hong Kong

Purpose

The study aims to investigate the characteristics of the current situation of library programs and explore the possible reasons behind the low participation in Hong Kong. It focuses on the development of library programs in the era of digital technology, which can lead to discussion and reflections on the further development of library programs with innovative technology services.

Design/methodology/approach

This study applied a mixed-method research approach to investigate the current situation of library programming and the reasons for low participation in Hong Kong. The first part analyzes the characteristics of library programs offered by the Hong Kong Public Libraries (HKPL) through data collection from the HKPL website. The second part of this study investigated the reasons behind the low participation in library programs through quantitative research through an online survey.

Findings

The findings show that current library programs were dominated by reading activities and children's programs to a great extent, which both users and non-users are not very interested in. Further, most respondents expressed more interest in cultural and leisure events and hands-on activities (especially new technologies related) than traditional library programming. Many lapsed and non-users chose not to attend the library programs for boredom and uselessness. As a result, there is a need for HKPL to adjust its services to stay relevant to the needs and interests of local communities.

Originality/value

Scant studies explored the reasons behind non-users of public library programs, especially in Asia. This research contributes to the literature by analyzing and proposing the characteristics of the current situation of library programs and exploring the possible reasons behind the low participation in Hong Kong.

Mapping the literature on the application of artificial intelligence in libraries (AAIL): a scientometric analysis

Purpose

Artificial Intelligence (AI) is an emerging technology and turned into a field of knowledge that has been consistently displacing technologies for a change in human life. It is applied in all spheres of life as reflected in the review of the literature section here. As applicable in the field of libraries too, this study scientifically mapped the papers on AAIL and analyze its growth, collaboration network, trending topics, or research hot spots to highlight the challenges and opportunities in adopting AI-based advancements in library systems and processes.

Design/methodology/approach

The study was developed with a bibliometric approach, considering a decade, 2012 to 2021 for data extraction from a premier database, Scopus. The steps followed are (1) identification, selection of keywords, and forming the search strategy with the approval of a panel of computer scientists and librarians and (2) design and development of a perfect algorithm to verify these selected keywords in title-abstract-keywords of Scopus (3) Performing data processing in some state-of-the-art bibliometric visualization tools, Biblioshiny R and VOSviewer (4) discussing the findings for practical implications of the study and limitations.

Findings

As evident from several papers, not much research has been conducted on AI applications in libraries in comparison to topics like AI applications in cancer, health, medicine, education, and agriculture. As per the Price law, the growth pattern is exponential. The total number of papers relevant to the subject is 1462 (single and multi-authored) contributed by 5400 authors with 0.271 documents per author and around 4 authors per document. Papers occurred mostly in open-access journals. The productive journal is the Journal of Chemical Information and Modelling (NP = 63) while the highly consistent and impactful is the Journal of Machine Learning Research (z-index=63.58 and CPP = 56.17). In the case of authors, J Chen (z-index=28.86 and CPP = 43.75) is the most consistent and impactful author. At the country level, the USA has recorded the highest number of papers positioned at the center of the co-authorship network but at the institutional level, China takes the 1st position. The trending topics of research are machine learning, large dataset, deep learning, high-level languages, etc. The present information system has a high potential to improve if integrated with AI technologies.

Practical implications

The number of scientific papers has increased over time. The evolution of themes like machine learning implicates AI as a broad field of knowledge that converges with other disciplines. The themes like large datasets imply that AI may be applied to analyze and interpret these data and support decision-making in public sector enterprises. Theme named high-level language emerged as a research hotspot which indicated that extensive research has been going on in this area to improve computer systems for facilitating the processing of data with high momentum. These implications are of high strategic worth for policymakers, library stakeholders, researchers and the government as a whole for decision-making.

Originality/value

The analysis of collaboration, prolific authors/journals using consistency factor and CPP, testing the relationship between consistency (z-index) and impact (h-index), using state-of-the-art network visualization and cluster analysis techniques make this study novel and differentiates it from the traditional bibliometric analysis. To the best of the author's knowledge, this work is the first attempt to comprehend the research streams and provide a holistic view of research on the application of AI in libraries. The insights obtained from this analysis are instrumental for both academics and practitioners.