Rise of the machines

From _New Scientist_, 18 October 2019

DeepMind AI beats humans at deciphering damaged ancient Greek tablets

By Gege Li

Artificial intelligence is learning to decipher damaged ancient Greek
engravings. The AI seems to be better than humans at filling in missing
words, but may be most useful as a collaborative tool, where researchers
use it to narrow down the options.

There are thousands of ancient inscriptions we already know about, with
dozens more discovered every year. Unfortunately, many have become eroded
or damaged over the centuries, resulting in segments of text being lost.
Figuring out what the gaps could be is a difficult task, involving looking
at the rest of the inscription and other similar texts.

Yannis Assael at DeepMind and his colleagues trained a neural network, a
type of AI algorithm, to guess missing words or characters from Greek
inscriptions, on surfaces including stone, ceramic and metal, that were
between 1500 and 2600 years old.

The AI, called Pythia, learned to recognise patterns in 35,000 relics,
containing more than 3 million words. The patterns it picks up on include
the context in which different words appear, the grammar, and also the
shape and layout of the inscriptions.

Given an inscription with missing information, Pythia provides 20 different
suggestions that could plug the gap, with the idea that someone could then
select the best one using their own judgement and subject knowledge. “It’s
all about how we can help the experts,” says Assael.

To test the system, the team hid nine letters of a Greek personal name from
Pythia. It managed to fill in the blanks. In a head-to-head test, where the
AI attempted to fill the gaps in 2949 damaged inscriptions, human experts
made 30 per cent more mistakes than the AI. Whereas the experts took 2
hours to get through 50 inscriptions, Pythia gave its guesses for the
entire cohort in seconds.

This shows the potential of AI-assisted restoration, says Thea
Sommerschield at the University of Oxford, who was part of the team. “The
reward is huge because it tells us about almost every aspect of the
religion, social and economic life of the ancient world,” she says.

Philippa Steele at the University of Cambridge agrees that Pythia could
assist restoration efforts, although humans would still be needed to put
the pieces together by eye and then decipher them before this could happen.

“It looks to me as though the highest success rates would be achieved when…
we are just missing small parts of a long text, or when there are plenty of
similar parallels for a newly discovered fragmentary text,” she says.

Reference: arXiv, arxiv.org/abs/1910.06262

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