Artificial Intelligence in archival and historical scholarship workflow: HTS and ChatGPT
This work addresses the problem of automating transcription and normalization in archival scholarship, but it is incremental as it applies existing AI tools to a specific historical dataset.
The study tested ChatGPT for normalizing text from 366 letters in an archive, finding that while it had some inaccuracies, the corrected texts met expectations, showing AI can enhance archival research by enabling analysis of large datasets.
This article examines the impact of Artificial Intelligence on the archival heritage digitization processes, specifically regarding the manuscripts' automatic transcription, their correction, and normalization. It highlights how digitality has compelled scholars to redefine Archive and History field and has facilitated the accessibility of analogue sources through digitization and integration into big data. The study focuses on two AI systems, namely Transkribus and ChatGPT, which enable efficient analysis and transcription of digitized sources. The article presents a test of ChatGPT, which was utilized to normalize the text of 366 letters stored in the Correspondence section of the Biscari Archive (Catania). Although the AI exhibited some limitations that resulted in inaccuracies, the corrected texts met expectations. Overall, the article concludes that digitization and AI can significantly enhance archival and historical research by allowing the analysis of vast amounts of data and the application of computational linguistic tools.