BIBLE HISTORY DAILY

Replacing Archaeologists with AI

Archaeologists create a semi-autonomous detection system

Can AI replace archaeologists? https://www.vpnsrus.com/, CC BY 2.0, via Wikimedia Commons

Although you probably won’t see robots walking around an excavation site anytime soon, that doesn’t mean some archaeological tasks are not already being handled by artificial intelligence (AI). Publishing in the Journal of Archaeological Science, a team of researchers from the University of Haifa has presented a new method to detect and record walls in archaeological contexts through drone imaging and artificial intelligence. Now, a task that could have taken days or even weeks can be done in a matter of hours.

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Mapping a Site

Although Indiana Jones’s wild search for artifacts might be the popular image of archaeology, in reality, one of the most important aspects of any excavation is the painstaking recording of details. And especially because archaeology is an inherently destructive science, it is these details that end up telling the story of a site. However, the size, funding, and expertise of an excavation team can make a significant difference in the level of recording, which will nearly always result in some important information being lost. This is especially a problem when it comes to recording building stones. As walls can be made up of hundreds if not thousands of stones, it is a highly time-intensive task to thoroughly record the details of each individual stone. As such, archaeologists often resort to simple sketches, ground plans, and photographs, which can overlook important details. Thanks to advancements in artificial intelligence and imaging technology, however, that might not be a problem for much longer.

The University of Haifa researchers developed a new semi-autonomous artificial intelligence system that can detect building stones and wall segments in archaeological contexts. The system uses meticulously collected drone imagery to generate a detailed map of an entire site. The AI then scans the composite image and identifies various archaeological features, particularly stone walls and features. From this, it can then compare the stones to an extensive database to suggest what stone features belong together. Despite this automation, however, the system leaves room for archaeologists to manually correct the scans in cases where their interpretations of a feature differ. Once the features have been identified, the system can run various algorithms to automatically compare the site with other sites in its database and propose possible dates for the site and the construction methods used in its formation.

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Although the system remains imperfect, it has the potential to significantly improve the speed of archaeological recording, particularly during survey work, where a team often covers a large area within a short period. Additionally, depending on the drone used, the system can achieve per-pixel resolution below 1 centimeter, and the programmability of drones enables a far more thorough record of the site than would be possible with a standard camera. Finally, when paired with mounted LiDAR or multispectral imaging equipment, this system has the potential to penetrate through heavy vegetation and even below the surface.

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