This report summarizes the activities and outcomes of a collaborative planning project supported by The Andrew W. Mellon Foundation and organized by University Libraries at Virginia Tech, in collaboration with Virginia Tech Center for Humanities and the National Archives and Records Administration (NARA). A diverse group of archivists, librarians, humanists, technologists, information scientists, and computer scientists were convened for a five-part online workshop series to discuss and plan how artificial intelligence and machine learning could be used to ensure public access to the massive and ever-growing collection of government records in the NARA digital catalog.

During the workshop, participants identified requirements, developed conceptual models, and discussed a work plan for a subsequent pilot project that would apply state-of-the-art tools and technologies to increase the effectiveness of archival programs and broaden public access to the important content in the NARA catalog. The workshop focused on humanistic and equitability issues of artificial intelligence and developing ethical, human-centered technology that promotes the public good. As such, the topic of intentional mitigation of AI bias was a thread that ran through the entirety of the workshop.