A groundbreaking study led by experts from Duke University in the US has utilized cutting-edge artificial intelligence (AI) technology to analyze hidden language patterns in some of the oldest books of the Bible. The research team focused on the Enneateuch, the first nine books of the Hebrew Bible, and identified distinct writing styles that indicate multiple authors or scribal groups contributed to these ancient texts.

According to Thomas Römer, a professor at the Collège de France, the team’s innovative approach revealed unique stylistic differences among the authors, even in the use of common words like ‘no,’ ‘which,’ or ‘king.’ The AI model developed for this study categorized the text into three main writing styles: The Priestly source, the Deuteronomistic History, and the Book of Deuteronomy itself.

Interestingly, while most sections aligned with these categories, the team encountered unexpected variations in the Ark Narrative in 1 Samuel that did not fit any of the identified writing styles, suggesting a potential unknown aspect of the Bible’s composition. The researchers believe that this method could also be applied to analyze other historical documents for authorship verification.

Shira Faigenbaum-Golovin, the mathematician leading the project, highlighted the interdisciplinary nature of the research, involving mathematicians, archaeologists, linguists, and computer scientists to blend scientific analysis with biblical studies. The team’s findings, published in the journal PLOS One, provide significant insights into the authorship of biblical texts and offer a valuable tool for resolving scholarly debates in this field.

Looking ahead, Faigenbaum-Golovin expressed optimism about applying the same methodology to explore additional ancient texts. The study’s collaborative approach between science and the humanities has been lauded for its innovative contribution to biblical scholarship and its potential to uncover new discoveries in the study of ancient literature.