DeepMind AI Beats Human Historians at Deciphering Ancient Texts

According to a new paper by researchers from DeepMind and the University of Oxford’s Faculty of Classics, AI can help restore, understand, and recreate ancient Greek texts that have been damaged and left with gaps that make them nearly impossible to understand. The work will be presented next month at the Empirical Methods in Natural Language Processing conference in Hong Kong.

The researchers used an algorithm named after Pythia, the woman who in Greek mythology was a vessel for Apollo’s prophecies. They found that it outperformed historians trained in restoring fragmented stone, clay, or metal tablets. While the historians hit about 43% accuracy after two hours, Pythia landed a nearly 70% accuracy rate after needing a few seconds.

It’s often difficult for historians to accurately restore ancient tablets because entire sections of symbols may have been wiped away over the years. Epigraphy, the field of study dedicated to piecing together the content of inscriptions using physical and environmental context, has limitations such as a historian’s own biases and fabrications. These factors, plus the complexity of accurately dating inscriptional evidence, all make epigraphic work incredibly difficult and time-consuming.

While Pythia could assist in radically improving ancient text restoration, it's just that—assistance. Humans still need to perform the archaeological excavation, piece together the physical inscriptions as best as they can, make out what the symbols, and decide which of Pythia’s guesses make the most sense.