Policy, Risk and Innovation: A Mixed-Methods Framework for Using AI to Foster Inclusion in Marginalized Communities in Bangladesh

This study examines how the adoption of artificial intelligence (AI) and the implementation of policies shape inclusive educational outcomes for marginalized learners in Bangladesh, using evidence from Sherpur Sadar Upazilla. A convergent mixed-methods design integrated a student survey (N = 213; seven institutions; March–September 2024) with qualitative data from 37 stakeholders (teachers and policymakers) collected through semi-structured interviews and focus group discussions. Quantitative findings show that AI tool adoption was the strongest predictor of a composite educational outcome score (β = 0.38, p < 0.001), followed by institutional support (β = 0.25, p = 0.01). In contrast, the policy implementation gap—defined as the mismatch between policy intent and on-the-ground delivery—was negatively associated with outcomes (β = −0.12, p = 0.04). Digital infrastructure quality was positively associated with the outcome but was not statistically significant in the multivariable model (β = 0.17, p = 0.12). The model demonstrated strong explanatory power (R² = 0.67; F(4, 208) = 42.3; p < 0.001). Disparity analyses revealed persistent urban–rural inequities in reliable internet access (94.6% vs. 69.7%) and device readiness, with tablet access emerging as a key enabler of advanced AI-supported learning. Qualitative results corroborated three binding constraints: limited teacher AI preparedness, affordability barriers, and trust concerns related to privacy and algorithmic bias. Building on these findings, the paper proposes a policy–innovation framework centered on localized AI toolkits, sustained teacher upskilling, device-access interventions, and enforceable fairness and transparency safeguards to advance equitable learning opportunities. Authors Ritesh Karmaker Dept. of English, Nizam Uddin Ahmed Model College, Mymensingh, Sherpur-2100, Bangladesh Author Vladimir M. Cvetković Department of Disaster Management and Environmental Security, Faculty of Security Studies, University of Belgrade, Gospodara Vučića 50, 11040 Belgrade, Serbia , Scientific-Professional Society for Disaster Risk Management, Dimitrija Tucovića 121, 11040 Belgrade, Serbia , Safety and Disaster Studies, Department of Environmental and Energy Process Engineering, Technical University of Leoben, Franz-Josef-Straße 18, 8700 Leoben, Austria , ProSafeNet, Global Hub For Safety, Security, Risk & Emergency Professionals & Scientists, Belgrade, Serbia Author https://orcid.org/0000-0002-3450-0658 DOI: https://doi.org/10.66050/scv48268 Keywords: hazards, artificial intelligence, government policies, marginalized communities, Bangladesh, inclusive education https://internationaljournalofdisasterriskmanagement.com/index.php/Vol1/article/view/237