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Decoding The Digital Fuku: Deciphering Colonial Legacies to Critically Assess ChatGPT in Dominican Education

Project Overview

The document examines the role of generative AI, specifically ChatGPT, in transforming the educational landscape of the Dominican Republic, highlighting both its potential benefits and challenges. It contextualizes the discussion within the historical framework of educational inequities stemming from colonial influences and stresses the necessity of critically evaluating AI technologies to prevent the reinforcement of digital colonialism. The document advocates for active involvement from local stakeholders in the implementation of AI tools to ensure that they promote equitable educational access while respecting cultural integrity and addressing inherent biases in AI systems. It underscores the importance of leveraging generative AI to enhance learning experiences while being mindful of the socio-cultural implications and potential risks associated with its use in education. Overall, the findings suggest that thoughtful integration of AI can contribute positively to educational outcomes, provided there is a concerted effort to align these technologies with the values and needs of the local context.

Key Applications

ChatGPT

Context: Dominican education system, targeting students and educators

Implementation: Integration of ChatGPT for accessing educational materials, personalized tutoring, and teacher training.

Outcomes: Widened access to educational materials, potential for personalized learning experiences, and administrative assistance for teachers.

Challenges: Risk of misinformation, biases against non-native English speakers, potential for plagiarism, and the need for critical assessment of AI tools within cultural contexts.

Implementation Barriers

Cultural and Contextual & Technical and Operational

Generative AI tools like ChatGPT are predominantly trained on data from the AI Global North, leading to biases that may not be relevant or applicable in the Dominican context. Additionally, AI-generated content may not accurately represent diverse linguistic and cultural contexts, resulting in the propagation of low-quality information.

Proposed Solutions: Empower local stakeholders to assess and contextualize AI tools to reflect their own histories and cultural values. Invest in diverse training data and enhance the digital literacy of educators and students to critically evaluate AI outputs.

Project Team

Anaelia Ovalle

Researcher

Contact Information

For information about the paper, please contact the authors.

Authors: Anaelia Ovalle

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

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