The rapid integration of artificial intelligence (AI) into educational systems has transformed teaching and learning practices, offering opportunities for personalization, efficiency, and data-driven decision-making. However, the widespread adoption of AI also raises significant ethical concerns, particularly regarding equity, fairness, and governance. This study aims to examine the ethical challenges associated with the use of artificial intelligence in education, with a specific focus on balancing technological innovation and educational equity. Employing a qualitative descriptive-analytical approach, the research is based on a systematic literature review of peer-reviewed journal articles, policy documents, and reports published by international organizations such as UNESCO, OECD, and the World Bank. The data were analyzed using qualitative content analysis to identify recurring themes related to access inequality, algorithmic bias, data privacy, transparency, human agency, and institutional governance. The findings indicate that while AI has the potential to enhance learning outcomes, its implementation often exacerbates existing educational inequalities due to uneven access, biased algorithms, weak data governance, and limited institutional accountability. The study concludes that ethical considerations must be integrated into AI design, implementation, and governance to ensure that innovation in education is inclusive, transparent, and socially responsible.
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