Date Archaeological Specimens Using Artificial Intelligence

By Supriya Mangalpalli

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An International research team led by Lund University in Sweden developed an AI-based method to analyze DNA and accurately date up to ten-thousand-year-old human remains

Schematic view of dating workflow using TPS (Credit: Sara Behnamian et al.,”Temporal population structure, a genetic dating method for ancient Eurasian genomes from the past 10,000 years”, DOI: 10.1016 / j.crmeth.2022.100270)

Researchers developed a method called Temporal Population Structure (TPS) that can detect date genomes that are up to 10,000 years old. The research studied almost approximately 5,000 human remains which were dated with amazing accuracy compared to the conventional method. The traditional method since the 1950s of dating human remains involved radiocarbon, which is based on the ratio between two different carbon isotopes. The accuracy was not reliable from the data obtained using radiocarbon dating. Hence, the research team developed a method that is AI-based which would interest archaeologists and paleontologists.

“Unreliable dating is a major problem, resulting in vague and contradictory results. Our method uses artificial intelligence to date genomes via their DNA with great accuracy, says Eran Elhaik, a researcher in molecular cell biology at Lund University. “We show that information about the period in which people lived is encoded in the genetic material. By figuring out how to interpret it and position it in time, we managed to date it with the help of AI,” says Eran Elhaik.

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The researchers do not want to replace radiocarbon dating with TPS but they want TPS to be used as a complementary tool in the paleogeographic toolbox. The TPS method can be utilized whenever there is uncertainty with data obtained from radiocarbon dating.

“Radiocarbon dating can be very unstable and is affected by the quality of the material being examined. Our method is based on DNA, which makes it very solid. Now we can seriously begin to trace the origins of ancient people and map their migration routes,” concludes Eran Elhaik.

Click here for the published Research Paper


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