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AI and Equity in Higher Education: Ensuring Inclusivity in the Algorithmic Classroom
Abstract
This thought-provoking chapter is systematic research based on theories from literature review and empirical data exploring AI's potential impact on educational equity in higher learning. The atuhors examine how AI-powered systems might inadvertently perpetuate biases, affecting marginalized students disproportionately. This chapter discusses institutions' responsibility to implement AI in ways that support inclusivity and diversity. In addition, it highlights initiatives that prioritize fairness and transparency in AI algorithms. AI systems can perpetuate existing biases if not designed with the right in mind. Additionally, if an AI system is not transparent about its decision-making processes, identifying or rectifying potential biases will be nearly impossible. Readers will gain a deeper understanding of AI's challenges and opportunities in reshaping education, focusing on ensuring that no student is left behind.
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