Breaking Digital Chains: Strategies to Mitigate GenAI's Neocolonial Impact on Education

CoE-EDP, VisionRICoE-EDP, VisionRI | Updated: 16-06-2024 10:42 IST | Created: 16-06-2024 10:42 IST
Breaking Digital Chains: Strategies to Mitigate GenAI's Neocolonial Impact on Education
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A study by Matthew Nyaaba, Alyson Wright, and Gyu Lim Choi from the University of Georgia, examines the impact of Generative Artificial Intelligence (GenAI) on global education, highlighting how it can perpetuate Western ideologies and lead to digital neocolonialism. This occurs through inherent biases within GenAI systems that favor Western cultural references, examples, and languages, thereby marginalizing non-Western students and their languages.

Cultural Bias and Marginalization in GenAI

GenAI often generates content that reflects Western perspectives, values, and ideologies. This cultural bias can alienate non-Western students by providing examples and references that are irrelevant to their backgrounds. For instance, when asked about the seasons in a year, GenAI tools like ChatGPT and Gemini typically mention the four seasons familiar in Western contexts, ignoring the diverse climatic variations in other regions, such as the two main seasons in West Africa or Southeast Asia. Additionally, GenAI's predominant use of Western languages makes educational content less accessible to speakers of indigenous languages. This limitation hampers the ability of students to learn in their first language, which is crucial for their cognitive development and understanding. For example, when prompted to provide a term in Gurune (a language from Upper East Ghana), GenAI tools often fail, highlighting their limited representation of non-dominant languages.

Economic Disparity and Data Exploitation

The cost of accessing advanced GenAI tools exacerbates educational inequality. Schools in wealthier regions or developed countries can afford the necessary infrastructure and funding to integrate GenAI, while those in poorer areas cannot. This disparity widens the educational gap, privileging students in affluent areas with superior educational tools and opportunities. Furthermore, the control of GenAI data by tech companies outside local contexts can lead to commercial exploitation without benefiting local students and their communities. This concentration of control echoes traditional colonial power imbalances, where dominant countries or corporations assert economic and cultural dominance over less technologically advanced regions. GenAI tools are primarily developed in Western regions, reinforcing ideologies and teaching principles that may not align with local perspectives. This dominance limits the diversity of thought in education, perpetuating a class divide within societies. For instance, a lesson plan generated by ChatGPT on environmental science might include materials and activities more relevant to Western contexts, such as access to individual computers, which may not be feasible for students in developing countries.

Human-Centric Reforms and Inclusive Design

To address the biases in GenAI, the authors propose human-centric reforms that prioritize cultural diversity and equity. This involves engaging local stakeholders from diverse backgrounds in developing GenAI tools to ensure they reflect a wide range of cultural perspectives and needs. Liberatory Design Methods (LDM) empower designers to embrace non-Western viewpoints and develop solutions that acknowledge the intricacies of marginalized identities. This approach ensures that technological solutions are relevant and beneficial to local communities, fostering inclusivity and cultural pluralism. Foresight by Design is another proactive approach involving anticipating and mitigating potential harms of GenAI by considering trends, emerging technologies, and social changes. It emphasizes the need to assess training data for biases related to ethnicity, gender, socioeconomic status, and geographic location to prevent perpetuating power imbalances. Creating GenAI development hubs in various regions, such as Africa, Asia, and Latin America, can diversify the perspectives contributing to GenAI technology. This decentralization ensures that local voices and contexts are considered, leading to more accurate and culturally relevant solutions.

Effective Prompt Engineering for Equitable Learning

Educators and students need to develop advanced skills in prompt engineering to harness the full potential of GenAI while minimizing biases. This involves crafting prompts considering local cultural contexts and specific educational needs, ensuring that the generated content is relevant and inclusive. The paper emphasizes the importance of recognizing and addressing the biases in GenAI to prevent digital neocolonialism. By adopting human-centric, liberatory design methods and decentralizing GenAI development, stakeholders can ensure that these technologies support inclusive educational practices. Effective prompt engineering and continuous research are crucial for adapting to advancements in GenAI and promoting a diverse and equitable educational experience for all students.

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