Jonathan Prag co-authors paper on using AI to transform study of ancient texts
Merton Tutor in Ancient History Professor Jonathan Prag is a co-author of Restoring and attributing ancient texts using deep neural networks, the cover article in the latest issue of the scientific journal Nature.
The paper presents Ithaca, a deep neural network for the textual restoration, and geographical and chronological attribution of ancient Greek inscriptions – in other words, the use of artificial intelligence (AI) to help ancient historians fill in the gaps in ancient Greek inscriptions on stone and other materials.
More than this, however, Ithaca is also capable of attributing inscriptions to their original location with an accuracy of 71% and can date them to within 30 years of their likely original date. In one test, Ithaca was put to work on a series of important Athenian decrees, traditionally dated by historians to before 446/445 BCE. New evidence recently presented by historians suggests the 420s BCE as a more appropriate time period. Remarkably, Ithaca’s average predicted date for the decrees is 421 BCE, aligning closely with the new evidence and demonstrating how machine learning might contribute to historical debates.
The project is an excellent illustration of the sort of collaboration between computer scientists (in this case Google’s DeepMind) and humanities scholars that is becoming increasingly common: it was led by Dr Thea Sommerschield (Marie Curie Fellow at Ca' Foscari University of Venice, and a former doctoral student of Professor Prag) and Dr Yannis Assael (Staff Research Scientist, DeepMind).
Professor Prag commented:
“The huge quantity of evidence from the ancient world, whether texts or objects, keeps on growing, and is increasingly beyond the scope of individual historians to master, even as we work to make sense of it and to make it more accessible. The application of AI to this data, as Ithaca demonstrates, presents incredible opportunities – ancient history has an exciting future.”
