Generative AI and Digital Neocolonialism in Global Education: Towards an Equitable Framework
Project Overview
The document explores the implications of generative AI (GenAI) in education, emphasizing its transformative potential while also addressing significant challenges. It highlights how GenAI can enhance personalized learning experiences, streamline administrative tasks, and provide instant feedback, thus improving educational outcomes. However, the document raises concerns about the biases inherent in GenAI technologies, which often mirror Western ideologies and inadvertently marginalize non-Western cultures and languages. This digital neocolonialism threatens to perpetuate existing inequalities in educational access and representation. The findings underscore the necessity for equitable frameworks and human-centric approaches in the development and implementation of GenAI tools. By prioritizing inclusivity and diversity, educators and policymakers can harness the benefits of GenAI while mitigating its risks, ensuring that it serves as a tool for empowerment rather than exclusion in the educational landscape.
Key Applications
GenAI tools for personalized learning, language acquisition, and research enhancement
Context: Applicable in K-12 and higher education settings, including language learning environments and academic research contexts, facilitating self-directed learning and instructional support.
Implementation: Utilization of generative AI tools like ChatGPT and Gemini for curriculum development, lesson preparation, providing contextually relevant language learning experiences, and assisting in academic research through data analysis and literature reviews.
Outcomes: Enhanced personalized learning experiences, fostered meaningful learner interactions, increased efficiency in research tasks, and improved access to large datasets.
Challenges: Over-reliance on GenAI can reduce critical thinking; potential inaccuracies in generated content; biases in outputs may oversimplify cultural contexts; reliance on flawed algorithms.
Implementation Barriers
Cultural Bias
GenAI often reflects Western ideologies, marginalizing non-Western perspectives and languages.
Proposed Solutions: Implement human-centric design approaches that prioritize cultural diversity and equity.
Economic Disparity
The cost of accessing advanced GenAI tools exacerbates educational inequality.
Proposed Solutions: Develop frameworks for equitable access to GenAI technologies and resources.
Technological Accessibility
Limited access to technology and internet services in developing regions restricts the use of GenAI.
Proposed Solutions: Decentralize GenAI development to include local voices and contexts.
Project Team
Matthew Nyaaba
Researcher
Alyson Wright
Researcher
Gyu Lim Choi
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Matthew Nyaaba, Alyson Wright, Gyu Lim Choi
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai