Artificial Intelligence and Historical Knowledge: Rethinking Sources, Methods, and Interpretation
Dr . Urmila N. Kshirsagar
Associate professor in History
Smt.M.G.kanya mahavidyalaya sangli
Mo 9970516671
Email kshirsagarurmila@yahoo.co.in
Abstract
The integration of Artificial Intelligence (AI) into historical research has begun to transform how scholars approach sources, methods, and interpretation. Traditionally, history has relied on textual, archival, and material evidence that demands labor-intensive collection and interpretation. With AI, vast datasets—ranging from digitized manuscripts to multimedia archives—can now be processed at unprecedented speed and scale. This research paper explores the role of AI in reshaping historical knowledge, focusing on three dimensions: sources, methods, and interpretation. First, it examines how AI-driven tools such as natural language processing, image recognition, and machine learning expand access to historical sources by uncovering patterns and hidden narratives in previously unmanageable datasets. Second, it analyzes methodological shifts, particularly the emergence of computational history and digital humanities, which combine traditional historiography with algorithmic analysis. Third, it evaluates the interpretive challenges and epistemological debates raised by AI, including issues of authenticity, bias, ethics, and the risk of over-reliance on algorithmic outputs. By critically assessing these dimensions, the study argues that AI does not replace human historical reasoning but rather augments it, offering new possibilities for interdisciplinary collaboration and more inclusive narratives of the past. The paper concludes that AI-driven approaches call for a rethinking of historical scholarship, demanding methodological rigor, critical engagement with technology, and a balance between human judgment and computational insights.
DOI link – https://doi.org/10.69758/GIMRJ/2509I9VXIIIP0073
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