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neta:studio_ai:news_show:019

A paper in Digital Scholarship in the Humanities proposes 'interpretive computing': using AI to support collaborative meaning-making rather than simply automate archival analysis. A case study using Civil Rights oral-history collections applies language models to thematic metadata, interview segmentation, and user-curated story paths, while keeping annotations editable by people.