Machine Learning and Archaeology

Silicon Valley Meets Mesopotamia

Archeology is a relatively obscure but deeply impactful discipline. Archaeology is critical to our understanding of human history. Moreover, the discoveries unearthed through archaeological work impact and help shape other intellectual disciplines such as politics, geography, demographics and more. In many ways archaeology is a foundational discipline that creates the base of data and historical context that many different fields rely on.

Archaeology has three core functions: surveying, excavation and analysis. Archaeologists work diligently to identify archeological sites, excavate them to find artifacts and structures and then analyze them. Archaeology is a resource-intensive, slow and highly manual field. Archaeological teams can number in the hundreds and archeological digs can last for years. For example over 1000 archaeologists will be working across 60 sites in the United Kingdom’s biggest archaeological excavation ever. The speed at which we can identify, excavate and analyze has long limited the rate at which archaeology — and in turn our understanding of human history — progresses.

However, a range of new archaeological techniques involving the application of machine learning to the archaeological process are being developed that promise to uncuff archaeology’s advancement…