Bridging the AI Education, Knowledge, and Skills Gap of Library and Information Professionals: Evaluation of the Innovation, Inquiry, Disruption, and Access (IDEA) Institute on Artificial Intelligence

Abstract

Artificial Intelligence (AI) is reshaping all sectors of society, including libraries. AI adoption in libraries has been gradual due to concerns and challenges, including ethical issues, maturity of the technology, insufficient AI education and training designed for library and information professionals, and gaps in AI education in library and information science (LIS) programs. This case study reports on the motivations, processes, and evaluations of the IDEA Institute on AI that was developed to equip two cohorts (Fellows) of information professionals who participated in the 2021 and 2022 IDEA Institute on AI with the foundational knowledge and skills to lead AI work. A multi-method approach was used to collect and analyze the evaluation data from multiple sources at different points of the IDEA Institute on AI. The IDEA Institute on AI applied an outcome-based planning and evaluation model and employed formative and summative evaluations using surveys and focus-group discussions. Fellows worked in various library and information environments, most in academic libraries. The case study results showed that the Fellows’ AI knowledge and skills increased substantially, their confidence greatly increased upon completing the IDEA Institute on AI, and they engaged in AI projects in their workplaces. They built awareness of AI issues and challenges and developed a comprehensive understanding of AI within the context of equity, diversity, inclusion, and accessibility. The Fellows’ supervisors were positive about the learning and experience their Fellows gained from the IDEA Institute on AI and their peers. The results of this case study have significant implications for developing AI professional development programs in the LIS field, providing exemplary AI education and training as AI technology evolves, including generative AI and large language models, and integrating AI into LIS curricula.

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