
Digital archeology uses technology for research, analysis, and documentation of discoveries. AI promises to take digital archeology even further with faster, more accurate, and less intrusive discovery, extraction, and analysis. Despite AI’s transformative potential, several challenges must be addressed to facilitate its widespread adoption in archaeology.
Traditional data collection and analysis tools and methods are labor-intensive and time-consuming. AI can capture and compute data from various sources, such as geographical information systems (GIS) and satellite imagery. It can also identify correlations in seemingly unrelated data points.
AI can catch details that the human eye might miss. It can also uncover and process patterns and links hidden within vast geographical and environmental data. For example, AI can process drone and satellite images and analyze them for signs of human activities.
Many archeological sites are located in remote or potentially dangerous areas. By combining AI with drones and other remote sensing and imaging tools, archeologists can explore archeological sites without deploying personnel.
Because of climate change and human activities, archeological finds aren’t always intact. But thanks to AI-powered 3D modeling, archeologists can reconstruct archeological sites without physical handling. AI can also piece together broken pieces. It can also help archeologists read the texts in fragile artifacts.
AI is also revolutionizing artifact analysis. Its image recognition technologies can identify artifacts faster and better than humans. Through machine learning (ML), AI models can be taught to recognize even the subtlest of textural differences in artifacts. X-ray and other imaging tools can also leverage AI to analyze images and reveal insights, such as what artifacts are made of.
In 2021, archeologists used robots to unearth key artifacts linked to the lost city of Pompeii through a project called RePAIR. The project highlights the use of AI-powered robots for retrieving artifacts.
Leveraging AI for site discovery and artifact analysis offers several benefits, including efficiency and cost-effectiveness. For example, archeologists can now focus their efforts and resources on high-probability areas.
Site and artifact preservation are just as important as discovery and analysis. Predictive modeling helps preserve sites by accurately identifying artifacts, reducing the need for extensive excavation. AI’s non-invasive approach preserves site and artifact integrity for current and future studies. In addition to handling large pieces more delicately and precisely than humans can, robots help mitigate excavation-related risks.
A real-world example of AI applications in digital archeology is its use to identify potential archeological sites in Mesopotamian regions. By employing pre-trained AI models, archeologists can process satellite imagery and identify sites with 80 percent accuracy. The system produces heatmaps on which archeologists base their surveys.
AI has also been instrumental in translating prehistoric languages. The Babylonian Engine is an AI project that uses neural machine translation (NMT) to translate Akkadian text into English. NMT is faster and more accurate at translating short to medium-length sentences.
Even with all the benefits and possibilities, AI applications in archeology are not without challenges. For example, the accuracy of information AI produces depends on the quality and completeness of raw data. Domain expertise is needed to ensure data integrity through rigorous verification. The same expertise is also required to evaluate output to eliminate human subjectivity.
AI is pushing the boundaries of digital archeology. By leveraging AI-based technologies such as predictive analysis and machine learning, archeologists can uncover secrets of the ancient world and enrich history.
