The following is an open course on Generative AI for libraries and includes the materials for teaching and the recordings.
In a rapidly evolving technological landscape, libraries are leveraging generative artificial intelligence to enhance their services and adapt to changing user behaviors and needs. "Navigating New Norms: Harnessing Generative AI for Library Services and Solutions" is a short course designed to equip librarians with the knowledge and skills needed to automate efforts in advancing analytics, creating content, and answering library users' questions. Register to embark on a journey exploring the nuts and bolts of generative AI, from its foundational concepts to practical applications in library settings.
Led by a team of esteemed experts, this course will cover the following: First, Trevor Watkins, Teaching and Outreach Librarian at George Mason University, will teach the historical context and development of generative AI, its intended purpose, and potential implications along with real-world examples. Second, Dr. Kellie Owens will share her expertise in data ethics and lead discussions on ethical concerns surrounding generative AI, data privacy, ownership, and security. The last two sessions move beyond theoretical understanding, offering hands-on experiences during practical sessions, providing participants with firsthand experience in utilizing common generative AI tools and learning about how to implement the use of these systems for library work on the front and back end. From cataloging to chatbots, participants will discover how AI is revolutionizing library services while learning about resources for continued learning and professional growth. Join us where innovation meets ethical responsibility on this transformative journey into the world of generative AI.
This presentation meets the NLM/NIH strategic plan goals of (a) accelerating discovery & advancing health by providing the tools for data driven research and (b) building a workforce for data-driven research and health. The presentation addresses health information resources and data and increasing health information access and use by including information about ethics and best practices for use of generative AI in libraries.
Class Objectives
By the end of the sessions, learners will be able to
- Define key concepts related to generative AI, including neural networks and deep learning.
- Apply real-world applications of generative AI in library settings.
- Apply best practices for effective utilization of generative AI systems.
- Evaluate ethical considerations and inclusion strategies in the deployment of generative AI library services and instruction.
- Develop next steps for integrating generative AI into library operations, leveraging use cases and discussions as inspiration for innovation.
Course Syllabus
Download a copy of the course syllabus.
Pre-Readings
Session 1
Fischer (2023). Generative AI considered harmful. CUI’23 Proceedings of the 5th International Conference on Conversational User Interfaces, 7, 1-5. https://doi.org/10.1145/3571884.3603756
Dunn, A. G., Shih, I., Ayre, J., & Spallek, H. (2023). What generative AI means for trust in health communications. Journal of Communication in Healthcare, 16(4). https://doi.org/10.1080/17538068.2023.2277489
Sætra, H. S. (2023). Generative AI: Here to stay, but for good? Technology in Society, 75, 102372. https://doi.org/10.1016/j.techsoc.2023.102372
Session 2
White House Office of Science and Technology Policy (2022) Blueprint for an AI Bill of Rights. https://www.whitehouse.gov/ostp/ai-bill-of-rights/
Bender, E. M., Gebru, T., McMillan-Major, A., Mitchell, M (2021). On the dangers of stochastic parrots: Can language models be too big? FAccT '21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610-623. https://doi.org/10.1145/3442188.3445922
Session 3
Sondos, M. B., Myrzakhan, A., & Shen, Z. (2024). Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4. https://doi.org/10.48550/arXiv.2312.16171
Anthropic. (n.d.). Prompt Engineering. https://docs.anthropic.com/en/docs/prompt-engineering
Mollick, E., & Mollick, L. (2023). Assigning AI: Seven approaches for students, with prompts. https://doi.org/10.48550/arXiv.2306.10052
Session 4
Lund, B. D., Khan, D., Yuvaraj, M. (2024). ChatGPT in medical libraries, possibilities and future directions: An integrative review. Health Information & Libraries Journal, 41(1), i-iv, 1-113. https://doi.org/10.1111/hir.12518
Session 1: Navigating A New Horizon: An Introduction to Generative AI and Its Transformative Potential with Trevor Watkins
The session provides an overview, historical context, and development of generative AI. Key concepts will be defined, and, in this session, learners will become familiar with what generative AI is made to do and what it was not exactly created for.
Learning Objectives
- Summarize AI and its subsets, distinguishing generative AI.
- Describe the historical context and major milestones toward the development of large language models and generative AI.
- Define key concepts: Large Language Models, Natural Language Processing, Deep Learning (Transformers), taxonomies and ontologies, structured knowledge, transformers
- Demonstrate familiarity with real-world examples of generative AI applications.
Materials
Recording
Speaker Bio
Trevor Watkins is the Teaching and Outreach Librarian at George Mason University. He leads a mini-team of two staff members on the Teaching and Learning Team, which engages in teaching, special projects, outreach, and library programming for George Mason University Libraries. His research interests include Artificial Intelligence (AI), AI literacy, Augmented Reality (AR), digital sustainability, and human-AI interaction. He is a professional member of IASSIST, IEEE, and ACM (SIGAI, SIGCSE). He is the Technical Lead and senior web developer for Project STAND. He is also the founder of Grey Alien Technologies, where he consults with public libraries, academic libraries, and BIPOC organizations about their technology needs. His current projects include the Black Squirrel GNU/Linux operating system, Cosmology of Artificial Intelligence, Mason's 3D AR/VR Tour, and MOCA (Mason-Libraries Orientation Conversational Agent).
Session 2 Ethical Considerations for Generative AI Now and In the Future with Dr. Kellie Owens
This session provides an overview of ethical concerns around generative AI, including data privacy and security. Specific things to keep in mind and potential processes for libraries will be shared.
Learning Objectives
- Engage with ethical considerations for AI in general.
- Describe data privacy and security concerns around generative AI.
- Develop guidelines around the ethical use of generative AI for your library
Materials
Recording
Speaker Bio
Kellie Owens is a medical sociologist and empirical bioethicist whose work focuses on the ethical use of health information technologies. She is particularly interested in understanding when and how new technologies worsen or improve health inequities. Her most recent projects explore the actionability of genomic data for healthy populations. She is also interested in developing better social and technical infrastructures to support artificial intelligence and machine learning (AI/ML) tools in healthcare.
Hands-On Experiences and Applications with Michael Flierl
In this session, participants will get practical experience with common Generative AI tools and engage in exercises practicing ways of making use of these tools, preventing and avoiding common pitfalls, and implementing out-of-the-box solutions.
Learning Objectives
- Distinguish between common dual-use foundational models
(e.g., GPT-4,Claude, Gemini, & Mixtral). - Recognize different prompt engineering techniques.
- Brainstorm and/or outline AI-assisted library services.
Materials
Recording
Speaker Bio
Michael’s advanced education includes a Master’s from Marquette University in Philosophy and an MSLIS from the University of Illinois at Urbana-Champaign. Michael joined University Libraries in 2019 as Visiting Assistant Professor and Information Literacy and Research Engagement Librarian. He previously held positions as Assistant Professor of Library Science and Learning Design Specialist as well as Information Literacy Instructional Designer at Purdue University.
Session 4 Employing Generative AI in Libraries with Fred LaPolla
This session will focus on the applicability of generative AI in libraries, including providing use cases and success stories. Participants will learn about leveraging AI in library programming, chatbots and virtual assistants in libraries, and future trends. The speaker will also share resources for continued learning and professional development.
Learning Objectives
- describe how generative AI can be incorporated into and enhance library services.
- explore how services can use generative AI such as for text generation, chat, and recommendation/ranking systems.
- identify the benefits and challenges of implementing generative AI in libraries.
Materials
Recording
Speaker Bio
Fred LaPolla is a member of NYU Health Sciences Library’s Data Services team and liaison to the Departments of General Internal Medicine and Clinical Innovation (DGIMCI) and Radiology. Fred also teaches Rigor and Reproducibility and R Programming in the Grossman School of Medicine Vilcek Institute of Graduate Biomedical Sciences. He is passionate about professional education and finding ways to facilitate learning around data collection, management, visualization and analysis.
Fred is the Data Education Lead; Research & Data Librarian and holds a Masters of Library Science (MLS) from Queens College, CUNY.