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

I-Corps：通过众包和自动人脸识别进行历史照片识别

• 批准号: 2221733
• 负责人: Kurt Luther
• 金额: $ 4.93万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2023-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2221733&HistoricalAwards=false
• 关键词: Corps; Historical; Photo; Identification; Crowdsourcing

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.

这个I-Corps项目更广泛的影响/商业潜力是开发一种技术，以产生重大的文化和经济价值，包括承认历史上被边缘化群体的贡献。虽然我们最初关注的是拍卖行、估价师和经销商的用户群体，但这项工作也适用于画廊、图书馆、档案馆和博物馆（GLAM）以及家谱协会收藏的大量身份不明的照片，这些机构通常人手不足，主要依靠捐赠者和外部研究人员来识别照片。此外，识别工作流程还可以扩展到美国内战时代以外的其他历史时期。最后，这项工作通过一个向学者和公众提供的商业平台，促进技术，艺术和历史之间新的跨学科联系。这个I-Corps项目是基于识别历史照片中未知人物的技术发展。这是一项具有挑战性的任务，由广泛的研究人员，包括记者，历史学家，策展人，系谱学家，档案管理员，经销商和收藏家。目前，这些研究人员主要依靠人工调查方法，例如翻阅数百页的参考书寻找潜在的匹配。基于人工智能的面部识别算法和众包为支持这一任务提供了希望，但必须克服误报、偏见和群体思维等关键缺点。这项工作探索了新颖的人类-人工智能协作技术，有效地和道德地将人类和人工智能的互补优势联合收割机结合起来，以支持历史人物识别。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。