This paper critically discusses how Generative Artificial Intelligence
(GenAI) might impose Western ideologies on non-Western societies, perpetuating
digital neocolonialism in education through its inherent biases and further
suggests strategies to mitigate these effects. Our discussions demonstrated
that GenAI can foster cultural imperialism by generating content that primarily
incorporates cultural references and examples relevant to Western students,
thereby alienating students from non-Western backgrounds. Also, the predominant
use of Western languages by GenAI can marginalize non-dominant languages,
making educational content less accessible to speakers of indigenous languages
and potentially impacting their ability to learn in their first language.
Additionally, GenAI often generates content and curricula that reflect the
perspectives of technologically dominant countries, overshadowing marginalized
indigenous knowledge and practices. Moreover, the cost of access to GenAI
intensifies educational inequality and the control of GenAI data could lead to
commercial exploitation without benefiting local students and their
communities. We propose human-centric reforms to prioritize cultural diversity
and equity in GenAI development; a liberatory design to empower educators and
students to identify and dismantle the oppressive structures within GenAI
applications; foresight by design to create an adjustable GenAI systems to meet
future educational needs, and finally, effective prompting skills to reduces
the retrieval of neocolonial outputs.

本文批判性讨论了生成型人工智能（GenAI）如何在非西方社会中强加西方意识形态，通过其固有偏见在教育中持续推行数字新殖民主义，并提出了缓解这些影响的策略。我们的讨论表明，GenAI 可以通过生成主要涉及西方学生文化参考和例子的内容来培育文化帝国主义，从而使非西方学生感到疏离。此外，GenAI 对西方语言的主要使用可能会边缘化非主导语言，使其难以获得教育内容，潜在地影响他们以母语学习的能力。此外，GenAI 经常生成反映技术主导国家观点的内容和课程，盖过被边缘化的土著知识和做法。此外，GenAI 的访问成本加剧了教育不平等，并且 GenAI 数据的控制可能导致商业利用，而并未使当地学生及其社区受益。我们提出了以人为中心的改革，以优先考虑 GenAI 开发中的文化多样性和公平性；解放性设计，赋予教育者和学生识别和瓦解 GenAI 应用程序中的压迫结构的能力；设计前瞻性，创建可调整的 GenAI 系统以满足未来的教育需求；最后，有效的提示技巧来减少新殖民主义产出的检索。