The map shows sites with raw materials the team used with the "Big Exchange" project. (Image Credit: S. Strohm)
Archaeologists from seven countries are using AI through their "Big Exchange” project to understand prehistoric and early historic people’s interactivity and networks. The project recorded thousands of sites with millions of finds in Europe and Asia.
"Archaeology, of course, does not find imprints of relationships in the ground. But we do find raw materials, such as flint, obsidian, jade, ivory, and even various metals, that have often traveled long distances from their sources to where they were found. They are like shadows of relationships between people. With their help, we can investigate networks in the past," says Dr. Tim Kerig, project leader and archaeologist in the ROOTS Cluster of Excellence at Kiel University.
Using raw materials and the associated raw material sources to analyze early networks has been done for approximately 50 years. "It has provided us with many valuable insights into the past. But because of the effort involved and the specialization of individual experts, for a long time, the studies only dealt with one raw material at a time," says Dr. Johanna Hilpert, an archaeologist at the Institute for Prehistoric and Protohistoric Archaeology of Kiel University.
With digitalization, researchers can perform complex analyses with multiple raw materials simultaneously. The “Big Exchange” project keeps all recordable raw materials, their find locations, and places of origin in the analysis, which can only be achieved with AI and network analysis. All these materials are sourced from the Middle Stone Age to antiquity.
This project managed to record over 6,000 sites containing millions of individual finds from Western Europe to Central Asia. The network analysis from this data enabled “statements to be made about how the simultaneous distribution of various goods is related to the more or less restricted access of the respective people to raw materials.” Additionally, it concerns social inequality and power relations.
The team also believes the project serves as a social experiment. "It is not just about feeding datasets into appropriate databases and having them analyzed automatically. We want to have archaeologists on board for every dataset," Dr. Kerig says. Archaeological datasets can vary widely, with some available in analog form. "That is why it is important to involve colleagues who know the underlying excavations or surveys in the analysis. We do not just want to analyze prehistoric networks, but we also want to build scientific networks and link archaeology with data science."
The researchers showed the first result in their paper. The Linear Pottery culture’s northwestern characteristics were standard for its epoch. But with the latest excavations, the “Big Exchange” project network analysis revealed that the product mix is a unique case. "We will probably experience even more surprises like this when we systematically analyze the available data," says Dr. Kerig.
Additionally, they think colleagues can participate in the “Big Exchange” project, contributing data sets. ”The more participation, the better we can understand past relationship and network dynamics," concludes Tim Kerig.
I hate to realize this... but jobs in archaeology and translation are about to be significantly disrupted by AI. Nothing is safe, it seems.
Have a story tip? Message me at: http://twitter.com/Cabe_Atwell