Events

Join us for a round table discussion on the capabilities and concerns around applying Machine Learning (ML) to computational research of cultural heritage collections. The program will consist of short presentations from each invited speaker, followed by an open discussion with the panel and audience.

Melanie Walsh and Connor Franklin Rey will talk about their research on data-driven diversity audits of public library collections, as well as the potential futures of these tools with large language models (LLMs).  Ben Lee will present his interdisciplinary research that brings together approaches from artificial intelligence, library and information science, and the digital humanities, to build and examine large-scale search systems for digital collections. While much computational research aims to remove bias from data and models, Lucy Havens will reframe the problem by arguing that data bias is inevitable. Drawing on theories and practices from the library and archival sciences, Havens will present on uses of ML to identify and communicate bias in data. David Christensen’s presentation topic will be the application of ML in readers’ advisory services, focusing on how it can enhance book recommendations while addressing the challenges of matching readers with suitable books and maintaining user privacy.

This event is sponsored by CALMA–The Center for Advances in Libraries, Museums, and Archives. 

Speakers

David Christensen, Data Analysis Lead, Seattle Public Library

David Christensen is a seasoned data analysis professional with over eight years of experience in library systems and business processes. As the Data Analysis Lead at Seattle Public Library, he specializes in program performance reporting, decision support, and open data initiatives, while also contributing to data science education and research projects.

Lucy Havens, Lucy Havens, LLC; Research Affiliate, Centre for Data, Culture & Society, University of Edinburgh

Lucy Havens is a data scientist, designer, researcher, and consultant passionate about improving the tools we use to search for and access information.  In January 2024, she completed her Ph.D. in Informatics at the University of Edinburgh, where she developed a natural language processing approach to identifying gender biased language in archival catalog metadata descriptions.  She is currently extending this research with Newcastle University Special Collections, while also consulting on equitable approaches to AI and other data-driven technologies.

Benjamin Charles Germain Lee,  Assistant Professor, University of Washington Information School. 

Ben Lee received his Ph.D. in Computer Science & Engineering from UW, which was supported by a National Science Foundation Graduate Research Fellowship in machine learning. He served as the inaugural Digital Humanities Associate Fellow at the United States Holocaust Memorial Museum, as well as a Visiting Fellow in Harvard’s History Department. Ben also served as a Kluge Fellow in Digital Studies and 2020 Innovator in Residence at the Library of Congress and the 2020-2021 Richard and Ina Willner Memorial Fellow in the Stroum Center for Jewish Studies at the University of Washington. 

Connor Franklin Rey (they/them), Assessment Librarian, San Diego State University Library

Connor Franklin Rey is an early-career librarian and a recent alumnus of the UW iSchool’s MLIS program. They use quantitative and qualitative research to evaluate library collections, services, and spaces to inform strategic decision-making, increase equitable access to library resources, and share the library’s story.

Melanie Walsh, Assistant Professor, University of Washington Information School

Melanie Walsh’s research interests include data science, digital humanities, literature, and library and information science. She investigates how data and computational methods shape contemporary culture — such as the publishing industry and public libraries — and how they can be used to understand culture in turn. Previously, Walsh was a Postdoctoral Associate in Information Science at Cornell University. She received her Ph.D. in English Literature from Washington University in St. Louis. She is also co-PI of the AI for Humanists project and the Responsible Datasets in Context project.