What is it about?
This paper presents a hybrid methodology that combines artificial intelligence (AI) with expert knowledge to identify, classify, and validate cultural heritage (tangible and intangible) in rural areas affected by depopulation. The system uses coordinated intelligent agents that automatically search for and process data from local documents and websites (such as Wikipedia), classifying heritage elements and comparing them with reference inventories validated by specialists. The methodology was tested in a pilot study in four municipalities in the province of Ávila (Amavida, Cardeñosa, La Torre, and Solosancho), demonstrating that, although fieldwork and expert supervision remain essential, AI significantly streamlines the cataloging and documentation of rural heritage at risk of disappearing.
Featured Image
Photo by Mario La Pergola on Unsplash
Why is it important?
The research addresses a critical problem in Southern Europe: the rapid and undocumented loss of cultural heritage due to severe rural depopulation. The most innovative aspect of this work lies in the automation of the data collection and cataloging process, reducing research tasks that typically require around 200 hours of expert work per municipality to less than one hour per location using the developed tool. Furthermore, it highlights both the significant scalability advantages that AI offers to municipalities with limited resources and its current limitations (for example, the difficulty in detecting intangible heritage, movable assets, or undigitized ethnographic architecture), demonstrating the need for collaborative and hybrid models combining technology and human experts.
Perspectives
I believe this development represents a fundamental step forward in democratizing and accelerating the conservation of territorial heritage in vulnerable areas. While AI does not replace historical judgment or the on-site interpretation of specialists, it acts as a decisive catalyst for reducing the administrative and technical workload. The real challenge for the future is not only to refine language models, but also to promote systematic campaigns for the digitization of local archives. Only by reducing the digital divide that plagues rural areas will we be able to ensure that these smart technologies help rescue our collective cultural memory from invisibility and oblivion.
Fernando Peral Fernández
Universidad de Salamanca
Read the Original
This page is a summary of: Artificial Intelligence for Cultural Heritage Characterization: Towards Scalable and Sustainable Territorial Inventories, Journal on Computing and Cultural Heritage, July 2026, ACM (Association for Computing Machinery),
DOI: 10.1145/3831365.
You can read the full text:
Contributors
The following have contributed to this page
