Libraries at University of Nebraska-Lincoln
Abstract
The study investigated how librarians working in various university libraries in Kwara State, Nigeria, adopt and use artificial intelligence. The study raised four research goals as well as four research questions. A descriptive survey method and random sampling techniques with 450 randomly selected librarians from Kwara State Universities, Nigeria, were used for the research. Five research assistants were trained on how to contact respondents and secure their consent before distributing the structured questionnaire designed by the researcher, who assisted in the tool distribution process. The researcher was able to retrieve 410 copies of the 450 questionnaires that were given to the respondents. However, the rate of return was 91%, which is a respectable amount. A self-designed questionnaire was used to elicit responses from the respondents, and a simple percentage was adapted for data analysis. The results showed that there was little adoption of AI in university libraries in Kwara State, Nigeria. The research also reveals that security scanning devices at the entrances and exits of university libraries are the most prevalent AI systems, while other AI systems such as bots, chatbots, face recognition, touch recognition, RFID technologies, humans, AI classification tools, machine-readable catalogs, and not smart AI features are still missing from the Kwara State University libraries. A self-designed questionnaire was used to elicit responses from the respondents, and a simple percentage ratio was adapted for data analysis. The findings revealed that AI has received minimal attention in university libraries in Kwara State, Nigeria. According to the study, the most common AIs are security scanning equipment at university library entrances and exits, followed by robotics, chatbots, face recognition, and touch recognition. RFID technologies, humanoids, AI classification tools, machine-readable catalogs, and AI smart features are still lacking in Kwara State's university libraries. The results of this study also indicate that librarians in a university library are aware of the many ways in which artificial intelligence can be applied to provide services. The results of the study indicate that obstacles to adoption include significant disruption caused by artificial intelligence in traditional library services, a lack of skills and a need for training prior to adoption, irregular power supply, and a lack of adequate infrastructure for adoption, among other problems. The study recommended the need to organize training for librarians to enhance their skills in using artificial intelligence to provide services, and the university administration and libraries should commit and provide the necessary support for the adoption of artificial intelligence by providing the necessary infrastructure to ensure its rapid implementation.