The alternative, radiocarbon dating, is not as accurate.

Researchers led by Lund University in Sweden have developed an AI algorithm that analyzes the DNA in human remains to date their age. The method is far superior to radiocarbon dating, which is widely used to estimate the age of carbon-based stuff up to 50,000 years old. The latter method is not always accurate, and also depends upon the quality and quantity of the material available for age testing. (The Register)

“There has been no major development in ancient dating remains since the development of radiocarbon dating 80 years ago,” Eran Elhaik, lead author of the study, published in Cell Reports Methods, and an associate professor at the department of biology at Lund University.

“This is the first method that offers a radically different approach in 80 years. It is based on the DNA sequence, which can now be sequenced more easily and accurately than before using very little amount of organic material. Because radiocarbon dates are subjected to many biases, archaeologists can use our methods freely and rapidly to get another estimate.”

The Lund AI technique, known as Temporal Population Structure (TPS), looks for genetic markers that have mutated over time to estimate age. TPS looks for tens of thousands of these types of markers to narrow down the age of a person’s remains.

The machine-learning-powered software was trained on these mutational patterns from remnants that have been dated already. Given a new DNA sample, it can predict how old it must be.

TPS is another method that archaeologists can use to date specimens, especially where the sample is inadequate for the conduct of radiocarbon dating.

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