Artificial intelligence for analyzing historical documents and deep learning: A methodology for historical research in the digital revolution

Abstract

The utilization of artificial intelligence in analyzing extinct scripts and ancient manuscripts constitutes a scientific revolution that has reinterpreted human history through advanced digital tools. Deep learning algorithms have contributed to the decipherment of Sumerian cuneiform texts through digital initiatives such as Ancient Mesopotamian Texts, relying on neural networks to distinguish similar symbols and reconstruct missing fragments. In Africa, digitization projects of the Timbuktu Manuscripts have enabled the preservation of Islamic written heritage and facilitated linguistic and chronological comparisons using multilingual Optical Character Recognition (OCR) technologies. In Europe, artificial intelligence has been employed to reconstruct the texts and architectural structures of the city of Pompeii through three-dimensional modeling and volcanic ash analysis. Moreover, AI has played a key role in uncovering traces of Amazonian civilizations using spatial mapping techniques and deep satellite image analysis. In the historical and security contexts, algorithms successfully deciphered the German Enigma machine and traced networks of the slave trade by analyzing ship data and dispersed archival records. These projects—spanning Europe, the Americas, and Africa—demonstrate that artificial intelligence has become an epistemic instrument for rewriting history and revealing layers of human heritage that could not have been accessed without the cognitive capabilities of modern technologies.