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The global pandemic has brought about significant changes in education, which have led to concerns regarding fairness and accessibility in a technology-driven learning environment. This article focuses on the use of Artificial Intelligence (AI) in education and examines the potential for bias in AI-powered tools. By using the example of a first-year engineering student from India, it demonstrates how standardized tests and limited resources can generate skewed data that AI algorithms with bias could perpetuate. Strategies such as using diverse datasets, implementing explainable AI models, and including human oversight mechanisms can help mitigate this bias. While acknowledging challenges such as cost and technical limitations, the article highlights the opportunities that AI presents for personalized learning that benefits all students. Lastly, the article stresses the importance of collaboration between educators, policymakers, and AI developers in order to create ethical and equitable AI tools. It concludes by advocating for a future in which AI empowers learners and fosters a fair and just learning environment, prompting readers to consider the potential and responsibility associated with AI in education.
M Poornesh (Wed,) studied this question.