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AI in the Archives
Thursday, August 27, 2026
11:00 a.m. – 12:00 p.m. (Pacific Standard Time)
AI is already reshaping how archives and libraries manage collections, but it's a tool, not a turnkey solution. In this session, Hannah Moutran offers a practical, ground-level look at using Large Language Models in metadata creation and archival workflows, drawn from real projects underway at UT Austin Libraries, including her work with the Southern Architect & Building News Collection, architectural image metadata, alt text generation, AI-assisted music cataloging, and an evaluation of an MCP-augmented search pilot with EBSCO.
The talk weighs the advantages of AI adoption, including backlog reduction and greater discoverability, against the disadvantages that come with it, from embedded bias to confidently incorrect outputs to the risk of an increased workload for archivists and librarians. Particular attention goes to privacy: what changes between using an API, a chatbot interface, or a local model.
The session closes with field-tested guidance aimed at practitioners who want to thoughtfully move forward with AI: calibration to archivist style, human-in-the-loop review, piloting on small non-sensitive collections, and documenting AI use transparently.
The cost is $10 for SCA members; $5 for student members; $20 for non-members; and $5 for unemployed or precariously employed individuals.
Presenters:
Hannah Moutran received her MS in Information Studies from The University of Texas at Austin and previously earned an MS in Publishing from New York University. Her work as a Library Specialist in AI & Metadata Processing at The University of Texas at Austin Libraries has focused on the application of artificial intelligence to metadata creation, cataloging workflows, and archival description. She designs and evaluates AI-assisted workflows in collaboration with stakeholders across library departments, with particular interests in human-in-the-loop systems, evaluation methodologies, and the integration of large language models into technical services practice. Her recent projects have explored AI-assisted metadata generation for large-scale music and architectural collections, as well as automated alt text generation. She was a member of the AI Music Cataloging team, which was recognized as a finalist for the 2026 Clarivate Library Innovation Awards, and she has presented her work through professional organizations and industry forums, including the Texas Conference on Digital Libraries and ASIS&T.
Registration is open until August 26. Online payment is required.
