Artificial Intelligence and Cultural Heritage Preservation: Technoethics and Innovative Preservation Strategies in Bujumbura, Burundi

Document Type

Book Chapter

Publication Title

Artificial Intelligence Applications for Human Well-being and a Sustainable Future

Abstract

The rapid advancement of artificial intelligence (AI) and computational technologies presents transformative opportunities to address the critical issue of cultural heritage erosion, particularly in regions grappling with significant preservation challenges such as Bujumbura, Burundi. This study introduces an innovative methodology for the preservation and revitalization of cultural identities through the application of AI-driven digital archiving techniques. While the research focuses on Bujumbura, its approach emphasizes global applicability, demonstrating how the Holistic Archival Personality Profiling Model (HAPPM) can serve as a scalable framework for cultural preservation in other post-colonial or resource-constrained regions. Central to this methodology is the use of large language models and advanced digital technologies for semantic classification of diverse archival materials—including government records, personal correspondences, and family memorabilia—digitized and enriched with biotags, chronotags, and geotags to create a comprehensive digital space-time continuum. Additionally, the study explores the role of AI in reconstructing spoken languages and dialects using historical linguistic principles, offering pathways to preserve and revive endangered cultural elements. By fostering interdisciplinary collaboration among experts in AI, cultural heritage preservation, and digital humanities, this research highlights the transformative potential of AI in bridging temporal gaps, enriching cultural narratives, and enhancing global appreciation of diverse human identities. The methodology outlined not only contributes to academic discourse but also offers practical insights for stakeholders worldwide, paving the way for a more ethical, inclusive, and sustainable approach to cultural heritage preservation.

Research Highlights

  • The Problem: Cultural heritage in Bujumbura, Burundi faces severe erosion due to political instability, fragmented archival infrastructure, and traditional preservation methods that prioritize official colonial records over personal, familial, and community histories.

  • The Method: James Hutson of Lindenwood University in St. Charles, Missouri implemented the Holistic Archival Personality Profiling Model, using optical character recognition, vector databases such as Pinecone and Weaviate, and fine-tuned GPT-4o models with Retrieval-Augmented Generation to apply biotags, chronotags, and geotags to physical and digital artifacts.

  • Quantitative Finding: The initial phase of the digitization initiative in Bujumbura, Burundi completed the processing of over 100,000 historical records.

  • Qualitative Finding: Semantic classification with spatial, temporal, and biographical metadata creates a searchable digital space-time continuum; fine-tuned large language models allow dynamic conversational access to historical archives; digital repatriation and multi-server redundancy frameworks correct colonial biases while preventing data obsolescence.

Publication Date

8-2026

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