From Data to Decolonial Peacebuilding: African Epistemologies, Indigenous Knowledge Systems, and The Reengineering of Digital Humanities and AI in Conflict Analysis

Abstract

This study examines the epistemic, methodological, and political effects of applying digital humanities and artificial intelligence (AI) to the analysis of conflict and peacebuilding in African contexts. It is situated within a growing critique of data-driven governance that highlights the persistent epistemic asymmetries inherent in computational systems. Although AI and digital humanities methods have broadened the analytical scope of conflict studies through large-scale text mining, predictive modelling, and networked data interpretation, their foundational architectures often rely on Eurocentric ontologies that prioritise abstraction, quantification, and universalism over contextually grounded systems of knowledge. In the African conflict landscape, layered histories, diverse epistemologies, and communal logics are embedded in all conflict processes; thus, such methodological approaches risk misrepresenting the nature and causes of violence and its trajectories, thereby undermining the potential for sustainable peacebuilding. Against this background, a key research question driving this inquiry is: how can African epistemologies and indigenous knowledge systems be systematically integrated into digital humanities and AI frameworks to reshape the analysis of conflict within decolonial and context-responsive notions of peace? Subsidiary questions explore how existing computational models often obscure or distort local meanings of conflict; whether and how indigenous interpretive frameworks, oral traditions, communal memory, cosmological narratives, and normative ethics can be translated into computationally legible forms without losing their epistemic significance; and what institutional and methodological adjustments are needed to embed such epistemologies within algorithmic infrastructures. The study aims to advance the concept of “decolonial computational peacebuilding” as an alternative analytical approach that challenges not only the use of local knowledge as supplementary data but also underscores epistemic subalternity by redefining the epistemological foundations of digital conflict analysis.

The study will employ a mixed-methods, multi-layered research design that combines computational analysis with interpretive, ethnographically-informed inquiry. The empirical approach includes three main data sources: (1) a corpus of conflict-related policy documents, peace agreements, and media texts that are analysed using advanced computational techniques such as topic modelling (LDA and BERTopic), sentiment and discourse analysis, as well as network mapping; (2) digital data collected from community-based platforms, oral history archives, and social media to create a narrative space reflecting indigenous perspectives on conflict and reconciliation; and (3) qualitative data from semi-structured interviews and focus group discussions with community leaders, peace practitioners, non-governmental organisations, and knowledge custodians within selected African conflict zones. Using a convergent-parallel framework, analytical procedures involve critically interpreting the outputs of computational methods through hermeneutic analysis, thereby highlighting discrepancies between algorithmic representations and lived experiences.

By supporting various forms of participatory design, algorithmic outputs can be continually recalibrated in line with cultural logics, thereby reducing certain forms of epistemic erasure and enhancing contextual fidelity. Emphasising reflexivity, co-production, and epistemic plurality, this approach redefines our methodology of viewing digital humanities and AI as dialogical rather than extractive tools. Overall, the study advances the process of reengineering conflict analysis by demonstrating how the intersection of computational accuracy with Indigenous epistemologies can produce practically robust, ethically sound, and decolonially sensitive frameworks for peacebuilding in Africa.