Library and Information Science

Permanent URI for this community${dspace.ui.url}/handle/20.500.12479/264

Browse

Browsing Library and Information Science by Subject "Algorithmic bias"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Integrating artificial intelligence-based technologies ‘safely’ in academic libraries: An overview through a scoping review
    (Taylor & Francis Group, 2024) Ngulube, Patrick; Mosha, Neema
    Background. Academic libraries are increasingly integrating artificial intelligence (AI), but there is limited understanding of how they can be “safely” integrated into their business model. Objective. This scoping review addressed the question on how much research has been conducted on ethical issues and perceived risks associated with the safe integration of AI technologies in academic libraries. Design. Between December 2023 and March 2024, online databases and a search engine were used to identify sources of evidence published before 2024 that focused on ethical concerns and risks to the integration of AI-based technologies. Eligibility criteria and a charting form guided data synthesis. Results. Nigeria provided the bulk of the studies. Many studies used the quantitative methodology at the expense of qualitative and mixed methods research approaches. The use of theoretical underpinnings was limited to 18% of the studies. Ethical issues with an impact on the planet were not evident as matters that were covered related to trust and the society. The perceived risk of losing jobs was widely covered at the expense of other perceived risks. Conclusion. Research on the safe use of AI technologies in academic libraries is still in its infancy. More research is necessary to understand the phenomenon.