Abstract
<jats:p>Artificial Intelligence (AI) is increasingly integrated into education and healthcare systems, offering transformative benefits such as personalized learning and precision medicine. However, the adoption of AI in these critical domains necessitates a strong emphasis on explainability and ethical considerations to ensure trust, accountability, and societal acceptance. This chapter explores the intersection of explainable AI (XAI) and ethical AI in education and healthcare, emphasizing how transparent and interpretable models can foster informed decision-making and equitable outcomes. It highlights current challenges, regulatory landscapes, and the role of interdisciplinary collaboration in developing AI systems that are both innovative and aligned with human values. By bridging trust, transparency, and innovation, the chapter provides a comprehensive framework for deploying responsible AI that benefits both learners and patients alike.</jats:p>