TLA Discussion Forum: AI as a Tool for Performing Arts Libraries and Archives, 8/21/2026 at 2-3pm EDT
Are you excited, curious, anxious, uncertain, or (insert adjective here) about AI and how it may impact your work in a performing arts library or archive? Join the Theatre Library Association’s Events and Programming Committee for their next online discussion, “AI as a Tool for Performing Arts Libraries and Archives,” as we welcome two colleagues who have been exploring some possibilities in their collections. Read more below for descriptions of the presentations and our colleague’s bios.
We welcome you to join us on Friday, August 21 from 2:00-3:00pm EDT. Bring your questions as we will engage in a Q&A session after the presentations. To register, please go to this form. The forum is available synchronously for all attendees, and a recording will be made available to TLA members afterwards. A Zoom link and Outlook calendar invite will be sent to registered RSVPs closer to the event. We look forward to seeing folks!
AI and Archives. Breakdowns and Breakthroughs
The past year has been a time of AI-powered breakdowns and breakthroughs for many archives and libraries, including the Wisconsin Center for Film and Theater Research (WCFTR) and Media History Digital Library (MHDL). In this presentation, WCFTR and MHDL Director Eric Hoyt will reflect on these milestones-both good and bad-and what they mean for cultural heritage organizations moving forward. The breakdowns have included server crashes due to LLM bots crawling the WCFTR’s websites, as well as federal funding terminations linked to the applications of ChatGPT to assess, target, and de-fund projects. Yet the breakthroughs using AI have been equally profound, allowing us to accurately recognize text, extract structured data, and segment different sections of page scans (e.g., headline, news story, advertisement). These advancements have enabled research breakthroughs, identifying significant patterns for the histories of film and theatre. By sharing these specific examples related to AI, we can facilitate productive conversations about the future of our work.
Eric Hoyt is the Kahl Family Professor of Media Production in the Department of Communication Arts at the University of Wisconsin-Madison and an Affiliate Faculty member of the Information School. He is the Director of the Wisconsin Center for Film and Theater Research and Media History Digital Library, which has digitized over 3 million pages of historic books and magazines for open access. His books include Hollywood Vault: Film Libraries before Home Video (2014) and Ink-Stained Hollywood: The Triumph of American Cinema’s Trade Press (2022), as well as the co-edited anthologies The Arclight Guidebook to Media History and the Digital Humanities (2016), Saving New Sounds: Podcast Preservation and Historiography (2021), and Global Movie Magazine Networks (2025). His work has been supported by $1.4 million in extramural grants from the ACLS, IMLS, NHPRC, and NEH.
Reformatting Our Data
There is much anxiety and discussion about the economic, environmental, and ethical costs of AI in the library and archives community at present. These concerns are valid, and yet by rejecting the technology as a whole, the community misses the opportunity to use the technology to accomplish deep backlog work that could make our materials more findable and usable. In this presentation, Doug Reside will discuss his experiments to convert existing data (programs, scripts, finding aids, and even software) locked in legacy media into more usable forms.
Doug Reside is the Curator of the Billy Rose Theatre Division at the New York Public Library for the Performing Arts, where he oversees archival acquisitions, the Theatre on Film and Tape Archive’s video documentation program, exhibitions, programs, and researcher support. He also founded a musical theatre writing program in 2013 for emerging theatre makers. Reside holds a PhD from the University of Kentucky (2006). His book, Fixing the Musical: How Technologies Shaped the Broadway Repertory, was published by Oxford University Press in 2023.