Bridging Educational Inequalities with Future AI in Advancing SDG 4 - Anwar, Ican (Jurnal Sistem Informasi dan Teknik Informatika (JAFOTIK), 2025)
Educational inequality remains a persistent challenge in many developing contexts, where limited resources, large class sizes, and high dropout rates prevent students from achieving their full potential. This study aims to explore how future applications of Artificial Intelligence (AI) can bridge these gaps and support the achievement of Sustainable Development Goal 4 (SDG 4) on quality education. The research adopts a mixed-methods approach, combining case study analysis of AI-driven initiatives with scenario-based calculations of potential benefits in time, cost, and student reach. By examining areas such as AI tutoring, automated grading, predictive dropout interventions, and personalized learning, the study highlights both the opportunities and limitations of AI in education. The contribution of this work lies in proposing a practical framework that illustrates how AI can reduce disparities, optimize resource use, and enhance inclusivity, ultimately offering a pathway toward more equitable and sustainable education systems.