Architectural Heritage and Artificial Intelligence: Diagnosis and Solutions Proposed by ChatGPT for Algerian Historical Monuments
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Fecha
2025Materia/s
Materia/s Unesco
1203.04 Inteligencia Artificial
1203.09 Diseño Con Ayuda del Ordenador
3308 Ingeniería y Tecnología del Medio Ambiente
Resumen
This study explores the potential of artificial intelligence (AI), specifically ChatGPT, in enhancing the conservation of Algeria’s architectural heritage. By analyzing photographs of historical monuments, the research evaluates ChatGPT’s ability to identify architectural styles, detect pathologies, and propose conservation strategies. The findings reveal that while ChatGPT demonstrates proficiency in recognizing architectural features and generating general descriptions, its accuracy in identifying specific pathologies remains limited, with a certainty rate of only 40%. The tool’s reliance on textual data rather than direct visual analysis, coupled with its inability to meet specific academic requirements such as word count and accurate referencing, underscores its current limitations. However, the study highlights the potential of AI to complement traditional conservation methods, particularly when integrated with comprehensive databases and expert validation. The research advocates for a hybrid approach, combining AI’s efficiency with human expertise, to address the challenges of heritage preservation in Algeria. This work contributes to the growing field of AI applications in cultural heritage, offering insights into both the opportunities and constraints of leveraging AI for sustainable monument conservation. © 2025 by the authors.
This study explores the potential of artificial intelligence (AI), specifically ChatGPT, in enhancing the conservation of Algeria’s architectural heritage. By analyzing photographs of historical monuments, the research evaluates ChatGPT’s ability to identify architectural styles, detect pathologies, and propose conservation strategies. The findings reveal that while ChatGPT demonstrates proficiency in recognizing architectural features and generating general descriptions, its accuracy in identifying specific pathologies remains limited, with a certainty rate of only 40%. The tool’s reliance on textual data rather than direct visual analysis, coupled with its inability to meet specific academic requirements such as word count and accurate referencing, underscores its current limitations. However, the study highlights the potential of AI to complement traditional conservation methods, particularly when integrated with comprehensive databases and expert validation. The research advocates for a hybrid approach, combining AI’s efficiency with human expertise, to address the challenges of heritage preservation in Algeria. This work contributes to the growing field of AI applications in cultural heritage, offering insights into both the opportunities and constraints of leveraging AI for sustainable monument conservation. © 2025 by the authors.





