Formulating an AI Integration Framework for Educational Institutions
Course Description:
The rapid integration of Artificial Intelligence (AI) in education offers transformative opportunities for personalized learning, instructional innovation, and administrative efficiency. However, it also introduces ethical challenges related to data privacy, algorithmic bias, academic integrity, and equitable access.
This paper presents a qualitative review of global and regional ethical AI frameworks—including those from UNESCO, the European Union, and the World Economic Forum—along with industry standards and academic literature. The review identifies core ethical principles such as transparency, fairness, accountability, inclusiveness, and privacy, which are foundational guidelines for responsible AI use in educational settings.
Beyond the literature synthesis, the paper incorporates practice-based insights from the phased development of an institutional AI integration strategy, illustrating how ethical principles can be operationalized into policies, training programs, and digital governance mechanisms.
The findings highlight the critical role of transformative digital leadership, stakeholder collaboration, and sustained upskilling in creating ethical, adaptable, and context-sensitive AI strategies. This study contributes to advancing responsible AI adoption in education by offering a consolidated review of ethical frameworks and actionable strategies for institutional implementation.
It concludes with recommendations for developing localized AI policies rooted in ethical standards, ensuring that the integration of AI enhances rather than undermines the core values of education.
Date & Time: July 4, 2025 | 8:30 AM - 9:15 AM