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Date of Award
5-6-2026
Document Type
Video Recording
Abstract
Metadata work is time-intensive, and transcription even more so, yet discovery and accessibility of digitized archival materials depend on accurate description and full text. Since October, the University of South Carolina's Digital Collections team has participated in JSTOR's Digital Stewardship charter program, testing and refining Seeklight, an AI tool for generating metadata and transcripts. The team has integrated Seeklight into descriptive workflows for photographs and manuscripts, and the tool has become central to the department's strategy for achieving accessibility of handwritten historical documents. This presentation shares findings on the tool's accuracy, efficiency, and impact on metadata and transcription practices.
Recommended Citation
Hoskins, Katie, "Digital Collections at USC Explores JSTOR Seeklight AI for Metadata and Transcription" (2026). 2026 Southeastern Conference (SEC) AI Library Summit. 23.
https://scholarsjunction.msstate.edu/sec-ai-2026/23
