Webinar Review: AI and Workforce Development in Libraries: Overcoming Barriers and Embracing Lifelong Learning 2024

Guest Post by Mairéad Mc Keown, Knowledge and Critical Capability Manager at Bord Bia - The Irish Food Board.

AI (Artificial intelligence) concept via Shutterstock

The recent webinar titled "AI and Workforce Development in Libraries: Overcoming Barriers and Embracing Lifelong Learning 2024" by Leo S. Lo, Dean at the University of New Mexico and President of the Association of College and Research Libraries (ACRL), provided a comprehensive overview of the integration of AI in libraries. This event, organised by the Long Island Library Resource Council, aimed to address the diverse needs of library professionals at various career stages, focusing on integrating AI technologies into libraries. In this Libfocus blogpost, I will review the key insights and implications from the webinar, highlighting the importance of AI literacy, the barriers to its adoption, and strategies to overcome these barriers.

Introduction to AI and Workforce Development in Libraries

Leo S. Lo began the webinar by introducing the concept of AI and its relevance to libraries. AI, or Artificial Intelligence, is a broad field of computer science focused on creating systems capable of performing tasks that typically require human intelligence, such as logical reasoning, learning, problem-solving, perception, and language understanding. Key components of AI include Machine Learning (ML), Deep Learning, Natural Language Processing (NLP), and Computer Vision. These technologies have the potential to revolutionise library operations in many ways, such as enhancing cataloguing, improving reference services, digital marketing, managing digital collections as well as many other activities.

The Importance of AI Literacy

One of the central themes of the webinar was the importance of AI literacy for library professionals. AI literacy is defined as “the ability to understand, use, and think critically about AI technologies and their impact on society, ethics, and everyday life”. Key components of AI literacy include technical knowledge, ethical awareness, critical thinking, practical skills, and understanding societal impact. Librarians have been teaching information literacy for years and are now equipping themselves to pivot to AI literacy.

Historical Parallels and the AI Adjustment Period

Figure 1: Hype cycle for Artifical Intelligence, 2024

Leo S. Lo drew historical parallels to illustrate the AI adjustment period, comparing it to past technological advancements that have been successfully navigated. He highlighted the Gartner Hype Cycle for AI, (see graph above) which studies the way trends evolve, noting that generative AI is past the peak of inflated expectations and is now heading into the trough of disillusionment. According to Chris Howard, Gartner’s Chief of Research, this phase is where the hard work takes place, figuring out how to make AI work effectively in real-world applications.

Key Findings from AI Literacy Studies

The webinar presented findings from two national AI literacy surveys conducted in the U.S. in May 2023 and June/July 2024. These surveys aimed to understand the baseline knowledge of AI among library professionals, identify gaps and opportunities, support professional development, and benchmark progress. The key findings of the first survey revealed a below-moderate self-rated understanding of AI concepts and familiarity with generative AI tools. There was a notable demand for training on advanced AI concepts, AI tools and applications, and addressing privacy and ethical concerns. About 34% of respondents had participated in any form of training or professional development, with a 74% strong emphasis on the urgency of addressing ethical and privacy issues. In the first survey only a minority strongly agreed that AI could be beneficial but by the time the second survey findings were revealed, a larger majority agreed that AI has the potential to significantly benefit library operations and the number of participants who had participated in any form of training or professional development had almost doubled at 66%.

Barriers to AI Adoption in Libraries

The webinar identified several barriers to AI adoption in libraries, including access to tools, knowledge gaps, time constraints, institutional issues, and personal reluctance. Limited availability of advanced AI tools, particularly in institutions without institutional subscriptions, hinders full engagement with AI technologies and can lead to a reliance on free tools which are limited. The lack of structured training leads to fragmented knowledge and reduced confidence in using AI tools. Balancing current workloads with the need to learn new technologies is challenging, leaving not a lot of time allocated to professional development. Institutional issues, such as lack of support from leadership and cultural resistance to adopting new technologies, may stifle innovation. Personal reluctance, including technological anxiety and resistance to change, may cause avoidance and delayed skill development.

Strategies to Overcome Barriers

To overcome these barriers, the webinar suggested several strategies. Experimenting with free and open-source AI tools while advocating for institutional subscriptions can help address the issue of access to tools. Implementing structured, step-by-step training programs and encouraging peer learning groups such as Communities of Practice, can bridge knowledge gaps. Introducing microlearning sessions and encouraging dedicated professional development hours for AI learning can help manage time constraints. Advocating for leadership buy-in through success stories of AI integration and fostering a culture of experimentation and risk-taking around technology use can address institutional issues. Addressing fears by demonstrating and emphasising AI as a tool to enhance, not replace, human roles, skills, creativity and productivity, and providing low-stakes opportunities to experiment with AI in daily tasks can help overcome personal reluctance.

Effective Adult Learning Strategies for AI Training

The webinar highlighted the importance of incorporating adult learning principles into AI training for library professionals. Indeed, this is applicable to AI training across industries. These principles include self-paced and flexible learning, collaborative/social learning, learning by doing, and experiential practical activities which have immediate relevance. Offering asynchronous online AI courses that staff can complete at their own pace and encouraging self-directed projects that incorporate AI tools can support self-paced learning. Creating team-based learning opportunities and using AI learning cohorts/sets can foster collaborative learning. Whilst forming Communities of practice can aid skill-building and responsible AI implementation through shared knowledge and experiences. Incorporating hands-on AI tool workshops and using live demonstrations and interactive exercises during training sessions can facilitate learning by doing. Tailoring AI literacy training to library-specific/functional use cases, such as enhancing cataloguing, improving reference services, digital marketing, or managing digital collections, can ensure practical, immediate relevance.

Case Study: University of New Mexico's GPT-4 Exploration Program

The webinar featured a case study on the University of New Mexico's GPT-4 Exploration Program, a pilot program launched in the summer of 2023. The program selected 10 volunteers from different units of the college, with varying levels of interest and prior AI knowledge. The college paid for the subscription fees of GPT-4 for the participants. The program was structured into three phases: Introduction and Training, Exploration and Experimentation, and Evaluation and Sharing. Participants worked on individual projects, utilising GPT-4 to address challenges or explore opportunities in their respective fields. The program outcomes included increased AI literacy and confidence, hands-on experimentation, and tailored projects. Interestingly the programme ran for 12 weeks. This timing aligns nicely with Microsoft’s finding about the 11 by 11 tipping point, whereby 11 minutes of time savings over 11 weeks is all it takes for most Gen AI users to feel the tool is useful and develop a habit that sticks.

Positive Outcomes and Participant Experiences

The GPT-4 Exploration Program resulted in significant positive outcomes and participant experiences. Pre-program assessments revealed a modest level of familiarity with generative AI tools. By the program's conclusion, the average familiarity rating had risen significantly, indicating a 54% increase in participants' comfort and proficiency with AI technologies. Testimonials from participants highlighted the transformative impact of the program, with AI being seen as a collaborator rather than a threat. Hands-on experimentation increased comfort with AI, prompt practice built critical skills, and tailored projects amplified engagement. However, challenges such as data privacy concerns, prompt engineering difficulties, and AI's lack of subject matter expertise were also noted.

Expanding the Upskilling Program

Building on the success of the GPT-4 Exploration Program, the University of New Mexico expanded the upskilling program to include AI for teaching, research, and Open Educational Resources (OER). In the summer of 2024, the program included AI for teaching faculty, AI for research using Scite.ai, and AI for OER. In the spring of 2025, the program plans to include AI for academic advising, with a cohort of 20+ academic advisors using generative AI for their work.

Conclusion

The "AI and Workforce Development in Libraries: Overcoming Barriers and Embracing Lifelong Learning 2024" webinar by Leo S. Lo provided valuable insights into the integration of AI in libraries. The importance of AI literacy, the barriers to its adoption, and strategies to overcome these barriers were explored. The case study on the University of New Mexico's GPT-4 Exploration Program highlighted the positive outcomes and participant experiences, demonstrating the potential of AI to transform library operations. By designing tailored training programmes which have leadership support, incorporating effective adult learning strategies and fostering collaborative communities of practice, libraries can equip their staff with the necessary skills and knowledge to embrace AI and future-proof their careers.

References:

Leo S. Lo, Transforming academic librarianship through AI reskilling: Insights from the GPT-4 exploration program, The Journal of Academic Librarianship (2024)

Leo S. Lo, Evaluating AI Literacy in Academic Libraries: A Survey Study with a Focus on U.S. Employees, College & Research Libraries (2024)

Leo S. Lo, AI and Workforce Development in Libraries: Overcoming Barriers and Embracing Lifelong Learning, Long Island Library Resources Council (2024)

Howard, C. It’s Here: The 2024 Gartner AI Hype Cycle Gartner (2024)

De Pretto, T. Digital Transformation and AI – Collaborating in the New Age of Work, Digital Leadership Forum (2024)

This blogpost was co-created with Microsoft Copilot.