This paper examines the complex relationship between generative artificial intelligence (AI) and educational equity, analysing both the opportunities and challenges presented by these emerging technologies in educational contexts. The paper begins by establishing fundamental distinctions between educational equality and equity, emphasizing how various socioeconomic, cultural, and systemic factors contribute to persistent educational disparities. It then provides a comprehensive overview of generative AI technologies, particularly focusing on Large Language Models (LLMs) and their applications in educational settings. The analysis reveals several promising applications of generative AI for promoting educational equity, including enhanced accessibility features for students with disabilities, personalized learning experiences, and the creation of Open Educational Resources (OER). The paper highlights how AI-assisted tutoring, incorporating Socratic dialogue methods, and AI-generated feedback systems can provide valuable educational support, especially in resource-constrained environments. These technologies demonstrate potential in breaking down traditional barriers to education by offering multilingual support, adaptive learning materials, and immediate feedback mechanisms. However, the paper also addresses significant challenges and risks associated with implementing generative AI in education. These include concerns about digital divides, both in terms of access to technology and digital literacy skills, as well as the potential for AI systems to perpetuate existing biases. The research emphasizes the importance of thoughtful integration of AI technologies in educational settings, suggesting that the most effective approach may be a balanced combination of human instruction and AI-supported learning. By examining these various aspects, the paper contributes to ongoing discussions about how to harness generative AI's potential while ensuring its implementation promotes, rather than hinders, educational equity. The findings have significant implications for educators, policymakers, and educational institutions working to create more equitable learning environments in an increasingly technology-driven world.
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