Navarro High School Library Collaboration
At the Navarro High School Library, the LADDER team is collaborating with school librarians to develop and deliver an educational program to prepare high school students for the important roles that AI will play in their careers and lives. Our main collaborator is Navarro Early College High School Librarian Emily Hersh, and we also collaborated with school library students enrolled in the iSchool’s School Library Certificate Program and with practicing school librarians via a workshop that we held at the Annual Meeting of the Texas Library Association. We ran the first version of the program in Fall 2023, and we will run an expanded version in Fall 2024.
Austin Public Library Collaboration
Public libraries, including the Austin Public Library, face challenges in managing data across multiple systems and effectively utilizing it to enhance public impact. Data librarianship efforts tend to focus on reporting data required by various stakeholders, but there’s a gap in translating raw data into meaningful stories that support decision-making. This project aims to address these challenges by improving data curation practices and enhancing the role of the public information office in leveraging data for service. We also plan to build a series of case studies that are built from open-ended interviews with librarians to identify data management practices, workflows, strengths, and shortcomings.
University of Texas Libraries Collaboration
Summer 2023 Project: Many academic libraries have started testing the utility of generative AI, from special collection descriptions to enhancing user services. In collaboration with the University of Texas Libraries, we are exploring how college students perceive the complementarity and value of responses provided by an academic library’s virtual reference service alongside AI-generated responses. The purpose of this project is to deepen our understanding of the potential for human-AI collaboration in virtual references. We anticipate that the results will suggest future research directions for incorporating AI in academic libraries while maintaining human intermediation in reference services.
Summer 2024 Project: The purpose of this project is to explore the values of academic library user services and connect stakeholders to design innovative AI integrations that align with these values. The study is divided into two phases. Phase 1 involves an online focus group with academic librarians in the U.S. The aim is to understand current perceptions and practices of AI in academic libraries, explore their visions for future library services, and identify potential issues. Phase 2 is a participatory workshop with UT Library staff and master’s students from the University of Texas at Austin School of Information. The workshop will provide a reflective and creative space to explore the potential of generative AI in enhancing user services at UT libraries. Through group discussions and activities, the workshop aims to develop a set of guidelines for AI practices in user services and formulate a conceptual model for Librarian-AI-User collaboration
