Explainable AI, LLM, and digitized archival cultural heritage: a case study of the Grand Ducal Archive of the Medici

Abstract Since the advent of modern computational technologies, libraries and archives have been harnessing the power of computers to produce electronic finding aids for our archival cultural heritage. Today, with the arrival of generative artificial intelligence (specifically, large language models or LLMs), there are new opportunities to post-process these finding aids and enhance access to archival heritage. In this paper, we present a case study of AI-assisted post-processing; we also show how AI can help unlock cultural heritage if combined with interactive data visualization. Our case study focuses on the Grand Ducal Archive of the Medici, partially digitized and electronically cataloged by the Medici Archive Project. We used generative AI to post-process the electronic catalog of the Medici's early modern period correspondence, developing a prototype visual finding aid. Throughout the paper, we present the post-processing steps and introduce the visual finding aid. In conclusion, we critically examine AI's application in the heritage sector and urge GLAM professionals to embrace the technology and open their collections for AI-assisted post-processing.