I-Corps: Historical Photo Identification with Crowdsourcing and Automated Face Recognition

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The broader impact/commercial potential of this I-Corps project is the development of a technology to generate significant cultural and economic value, including recognizing the contributions of historically marginalized groups. While we initially focus on the user groups of auction houses, appraisers, and dealers, this work can also apply to the vast volume of unidentified photos in the collections of galleries, libraries, archives, and museums (GLAMs) and genealogical societies, which are generally short-staffed and largely rely on donors and outside researchers to identify photos. Further, the identification workflow can also be extended beyond the American Civil War era to other historical time periods. Finally, this work fosters new, interdisciplinary connections between technology, art, and history through a commercial platform made available to both scholars and the general public.This I-Corps project is based on the development of technology identifying unknown people in historical photographs. This is a challenging task performed by a broad range of researchers, including journalists, historians, curators, genealogists, archivists, dealers, and collectors. Currently, these researchers largely rely on manual investigative methods such as paging through hundreds of pages of reference books looking for a potential match. AI-based facial recognition algorithms and crowdsourcing offer promise for supporting this task, but key shortcomings, such as false positives, bias, and groupthink, must be overcome. This work explores novel human-AI collaboration techniques that effectively and ethically combine the complementary strengths of human and artificial intelligence to support historical person identification.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.