Artificial Intelligence (AI) is transforming educational decision-making by enabling data-driven processes in admissions, assessment, personalised learning, and institutional management. While AI systems promise efficiency, scalability, and objectivity, they also raise serious ethical concerns related to bias, transparency, accountability, data privacy, and equity. This paper critically examines the ethical challenges associated with AI-driven decision-making in education. It explores algorithmic bias, surveillance risks, data governance issues, and the implications for marginalised learners. The study also proposes a framework for ethical AI implementation grounded in fairness, explainability, human oversight, and policy regulation. The findings emphasise that AI must complement—not replace—human judgment in educational contexts to ensure inclusive and equitable outcomes.
Gurmeet Singh (Fri,) studied this question.
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