A team of experts has utilized cutting-edge artificial intelligence (AI) technology to uncover hidden language patterns and potential authors of some of the oldest books in the Bible. Led by Duke University in the US, the international group of researchers delved into the Enneateuch, the first nine books of the Hebrew Bible, employing advanced linguistic analysis and a custom AI model. Their analysis unveiled distinct writing styles within the texts, indicating multiple authors or groups behind the sacred scriptures.
According to Thomas Römer, a professor at Collège de France, each author group exhibited unique styles, even in common words like ‘no,’ ‘which,’ or ‘king,’ which the AI model could accurately differentiate. The project, initiated by mathematician Shira Faigenbaum-Golovin in 2010 with a focus on ancient pottery inscriptions, aimed to shed light on the origins of Old Testament texts by assembling a multidisciplinary team of experts.
The AI model identified three main writing styles within the texts: The Priestly source, the Deuteronomistic History, and the Book of Deuteronomy itself. While most sections aligned with these categories, surprising discrepancies were found in the Ark Narrative of 1 Samuel, suggesting additional unknown contributors to the Bible’s composition. The team believes this methodology could be extended to analyze other historical documents for authorship verification.
Faigenbaum-Golovin, leading a diverse team of specialists, envisions further applications of this technique to explore other ancient texts. The study’s findings, published in the journal PLOS One, offer significant evidence of distinct linguistic features in biblical writings, providing a valuable tool for resolving debates in biblical studies. This innovative collaboration between science and the humanities has the potential to unveil new insights into ancient texts, showcasing the power of interdisciplinary research.
