The Dead Sea Scrolls have long provided us with a treasure trove of ancient religious manuscripts. Ever since their discovery in the middle of the 20th century, they have puzzled historians and archaeologists. An international team of researchers has recently employed artificial intelligence (AI) combined with traditional methods to refine the dating of these significant artefacts. Their findings suggest that most scrolls date from earlier than had been established for them, possibly changing the perceptions of the broader historical context of these works.
Scholars and archaeologists excavated the scrolls from the Qumran caves in the West Bank between 1946 and 1956. These ancient texts, primarily in Hebrew, but in Aramaic, Greek, Latin and Arabic. These ancient manuscripts—hand-copied Buddhist texts—date between 2,500 and 1,800 years old. Less than 10 percent of them have explicit dates that indicate when they were written.
One of the most well-known finds is a fragment of the Book of Daniel. Right now, carbon dating indicates it’s from sometime between 230-160 BC. This study is a first in many ways. Most importantly, it will change the way we think about the creation and dissemination of these texts.
Innovative Methods Employed
The research team utilized a unique combination of AI technology, carbon dating, and handwriting analysis to address gaps in the timeline of the Dead Sea Scrolls. Under the direction of professor Popović, the initiative suggested new ages for more than 100 scroll fragments. These state-of-the-art methods enable researchers to collect more precise data non-invasively, preserving the fragile manuscripts in the process.
“AI analysis of the digital images of the scrolls does not destroy them,” – Professor Popović.
Dr. Wearne, another major researcher on the study, commented on how groundbreaking these findings truly are. He stated this research represents “the single greatest step forward since the development of the original, conventional dating system” that emerged in the 1940s.
The team was met with enormous difficulties using conventional forms of radiocarbon dating. Often, contamination affects these methods making them less accurate or providing inconclusive results. AI integration offers a better, more consistent way to assess quality.
Andrea Jalandoni, a researcher involved in the project, noted that this new approach allows for comprehensive evaluations. “They’ve pinned it with radiocarbon and then evaluated it with expert palaeographers.”
Implications for Historical Understanding
This research is much more than even dating the scrolls. It raises truly fascinating questions as to why and how these texts come to their final forms and what they’re doing there in the biblical canon. Dr Wearne stressed that by knowing the dates of these manuscripts, it offers a greater insight into their passage through history.
“It potentially has implications for how we think about how the material came to be copied and disseminated at the beginning of the process that ultimately led to them being included in the biblical canon,” – Dr. Wearne.
Researchers recently found that two of the scrolls may preserve texts composed upon their original emergence. Such a finding would imply they are almost as progressive as when they were created. This surprising find upends previous beliefs about when and where these important religious texts were produced.
The study’s success indicates that similar methodologies could be used on other historical documents. Professor Popović noted that “the techniques and methods we developed are applicable to other handwritten collections of text.” This promises to be an exciting new frontier for scholars of many disciplinary stripes who study ancient texts.
Future Directions in Archaeology
As scientists continue to raise the bar for these techniques, there’s promise of even more exciting breakthroughs in dating artefacts from the deep past. Andrea Jalandoni expressed excitement about the possibilities: “Wow, I wonder if I can do this with rock art.”
At present, although there are other dates for rock art, it is still few and far between. Jalandoni is determined that by creating a machine learning model, they can predict dates with multiple methods. This change would be a huge step in the right direction in this area.
“If we could … create a machine learning model that can predict dates that line up with more methods, I think it’s the way to go,” – Andrea Jalandoni.
This interdisciplinary effort between archaeologists, historians, and AI experts exemplifies the power of technology to deepen our understanding of complex historical narratives. As this research continues, it holds the potential to incite more investigation into the ancient texts and their historical contexts.
