Why the future of archaeology lies in the interaction between human and artificial brains

Mauritzio Forte | Unlocking Digital Archaeology · 58:29 · Video: The Institute for the Study of Ancient Cultures · Watch at the source

In short: We are moving beyond simply recreating the past to performing it. Through the integration of artificial intelligence and neuroarchaeology, researchers are developing new ways to simulate ancient landscapes, transforming how we interpret the rise and decline of ancient cities.

The field of digital archaeology has undergone a significant evolution through three distinct milestones: Virtual Archaeology in 1996, Cyberarchaeology in 2008, and the more recent emergence of AI-Archaeology in 2022. At the heart of this progression is the power of simulation. Rather than merely producing static images, these domains rely on complex models where human cognition and computational intelligence interact to produce deeper, more informative layers of historical data.

Maurizio Forte, the William and Sue Gross Distinguished Professor at Duke University, is at the forefront of this shift. As the director of both the DIG@Lab and the Archaeo-Drone lab in Chianciano, Italy, Forte explores how digital tools can study the transformation and decline of ancient urban centers and landscapes. His work spans several specialized disciplines, including Etruscan, Pre-Roman, and classical archaeology, often utilizing neuroarchaeology to study how the human brain perceives virtual models of material culture.

The ultimate goal of this research is to move toward a generative-autopoietic system. In this future state, AI-archaeology could function as a system that generates its own digital codes, syntaxes, and hypotheses. This approach addresses the inherent subjectivity of historical interpretation. Because archaeological truth is often ambiguous, researchers do not simply recreate the past; they 'perform' it. By generating vast numbers of virtual situations, scholars can continuously reinterpret monuments, relics, and landscapes. This generative process may eventually solve the 'unsolvable' challenge of 4D representation, allowing us to view the past not as a fixed point in time, but as a fluid, continuous, and co-evolving process.

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