IArch: An AI Tool for Digging Deeper into Archaeological Data

The use of Artificial Intelligence (AI), notably Machine Learning (ML), is gaining momentum in archaeology, opening up new possibilities such as artifact classification, site location prediction, and remains analysis. One of the major challenges in this regard is the lack of qualified archaeologists who are experts in machine learning. In this study, we introduce IArch, a tool that enables eXplainable Artificial Intelligence (XAI) data analytics for archaeologists without requiring specific programming skills. It specifically allows data analysis performed to either validate existing data-supported hypotheses or generate new ones. The tool covers the entire workflow for applying ML, from data processing to explaining the final results. The tool allows the use of supervised and unsupervised ML algorithms, as well as the SHapley Additive exPlanations (SHAP) technique to provide archaeologists with global and individual explanations for the predictions. We demonstrate its use on data from a Xiongnu cemetery (100 BC/AD 100) in the Mongolian steppes.