Harnessing Artificial Intelligence (AI) in African Historiography: Augmenting Historical Sources

Vollständiger Abstract

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Artificial Intelligence (AI) has emerged as one of the most transformative technologies of the twenty-first century, rapidly reshaping academic fields and research methodologies. In African historiography, where oral traditions, written document, archaeological materials and historical linguistic form the core foundations of historical sources. Artificial intelligence offers unprecedented opportunities for enrichment, preservation and reinterpretation of human past. African history has long been shaped by fragmented archives, limited documentation, colonial distortions, and the vulnerabilities of orally transmitted memory. This study adopts a mixed-methods approach that combines qualitative archival and oral-historical methods with computational techniques, reflecting the interdisciplinary nature of integrating AI into African historiography, draws on secondary sources to analyze the AI factor in historical research and documentation. AI presents complementary tools that strengthen these sources: speech recognition models help preserve and transcribe oral narratives; machine learning corrects and deciphers ancient manuscripts and Ajami texts; satellite-based AI enhances archaeological discovery; and computational linguistics reveals hidden historical relationships embedded in African languages. This paper examines how AI can serve as a complement rather than a replacement to traditional historical methods. Through theoretical engagement, methodological analysis, and empirical examples from across Africa, it demonstrates how AI expands the historical sources, safeguards endangered knowledge systems, and empowers African scholars and communities to reclaim historical narratives. The paper acknowledges limitations and ethical concerns, emphasizing the need for community participation in historical reconstruction, decolonized digital practices and human interpretative authority.