Eye on ML in archaeology

Machine learning is finding more and more applications in archaeology, although not all researchers are excited about it.

“There are two distinct belief systems,” says Hugh Thomas, an archaeology lecturer at the University of Sydney and co-director of the prehistoric AlUla and Khaybar excavation project in Saudi Arabia. 

On one side, people are pursuing technological solutions like AI to identify sites; on the other, those who believe you need a “trained archeological eye” to identify structures, he explains.

While technology could help identify and monitor archaeological sites —particularly ones under threat from land use changes, climate change, and looting —Thomas is wary of over-reliance on it.

“The way that I would like to use this kind of technology is on areas that perhaps have either no or a very low probability of archaeological sites, therefore allowing researchers to focus more on other areas where we expect there to be more found,” says Thomas.