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Author: search.filters.author.Aziz, TamoorSubject: search.filters.subject.AI

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    An AI-integrated framework for sustainable conflict mitigation and policy innovation
    (2026-09-01)
    Tissamana, Apinya
    ;
    Ajayi, Babatunde Oluwaseun
    ;
    Bamisaye, Mayowa Emmanuel
    ;
    Katerenchuk, Wendell
    ;
    Aziz, Tamoor
    Conflict in Thailand's peripheral regions remains a persistent challenge, particularly in provinces such as Ubon Ratchathani, where inequalities, cultural marginalization, and resource pressures intersect to shape local tensions. Despite growing attention to conflict analysis, existing approaches often struggle to combine contextual understanding with predictive capability, limiting their usefulness for timely and effective policy intervention. To address this gap, this research introduces a hybrid framework integrating the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method with the Random Forest (RF) algorithm. Using primary data from 400 respondents across urban and rural communities in Ubon Ratchathani, the framework combines stakeholder-informed causal mapping with data-driven prediction. DEMATEL identifies and structures relationships among key conflict dimensions, while RF evaluates and predicts these relationships using empirical data. The findings reveal that cultural and identity issues are the primary drivers of conflict, shaping political and economic marginalization, whereas resource-related conflicts emerge as downstream effects. The RF model demonstrates excellent predictive performance (MSE = 0.0120; RMSE = 0.1097), indicating that these relationships can be reliably translated into predictive insights. This enables policymakers to move beyond reactive responses toward early identification of conflict risks and more targeted interventions. Effective interventions, however, must be coordinated across sectors and tailored to local contexts to achieve lasting impacts. By linking causal understanding with predictive capability, the proposed framework offers a practical tool for conflict monitoring and more inclusive governance aligned with the Sustainable Development Goals (SDGs). While promising, the framework should be tested in other regions to assess its broader applicability.