Determining by means of paleography the chronology of ancient handwritten manuscripts such as the Dead Sea Scrolls is essential for reconstructing the evolution of ideas, but there is an almost complete lack of date-bearing manuscripts. To overcome this problem, an international team of scientists created an AI-based date-prediction model — named Enoch, after the Biblical figure — trained on the basis of 24 dated scroll samples.
While some ancient manuscripts have dates written on them, giving archaeologists a precise understanding of when they were created, many manuscripts have no date information.
By studying the evolution of handwriting styles over time, researchers can sometimes determine the approximate age of some undated manuscripts by evaluating their handwriting.
But to use this method, researchers need enough manuscripts with accurate dates from that period of history to create a reliable timeline of handwriting styles.
In a new study, Dr. Mladen Popović from the University of Groningen and his colleagues evaluated the age of historic manuscripts from various sites in modern-day Israel and the West Bank through radiocarbon dating, and then used machine learning to study the handwriting styles of each document.
By pairing those two datasets together, they created the Enoch program that uses the handwriting style of other manuscripts from the region to objectively determine an approximate age range.
To test the program, ancient handwriting experts evaluated Enoch’s age estimates for 135 of the Dead Sea Scrolls.
The experts determined that approximately 79% of the AI’s estimates were realistic, with the remaining 21% determined to be either too old, too young, or indecisive.
Enoch has already helped the research team discover new things about these ancient manuscripts.
For example, both Enoch and radiocarbon dating methods estimated older ages for many of the Dead Sea Scrolls than did traditional handwriting analysis.
“Although more data…
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