Western-Centric AI Ethics Framework Disconnected from African Realities In modern society, Artificial Intelligence (AI) plays a role beyond mere technology. Initially making its presence felt as a debate partner or video recommendation model, AI is now expanding its influence across legal, economic, and social spheres, demanding regulatory and ethical discussions. However, it is increasingly evident that this AI governance, designed from a global perspective with a Western-centric focus, is neglecting the practical needs of non-Western regions like Africa. This situation not only highlights the ethical dimensions of technological advancement but also sharpens the issue of global inequality. The 2nd African Cyber Law Conference, recently held at Wits University, directly addressed these concerns. During the conference, Dr. Nomalanga Mashinini, Senior Lecturer at Wits Law School and conference organizer, strongly criticized the systemic exclusion resulting from AI training on Western-centric datasets. She stated, "We see this phenomenon in the real world where Africans are not represented in technology design, which raises questions about who is seen, who is excluded, and who is protected within digital systems." Dr. Mashinini specifically cited instances where AI systems fail to detect harmful content in African languages, miss cultural nuances, or misclassify and render invisible entire populations. This problem arises because AI systems are predominantly trained on Global North datasets, leading to underrepresentation of African languages, loss of cultural subtleties, and the inaccurate classification or invisibilization of entire populations. This underscores the need for legal and ethical regulations to protect individual rights, as well as the necessity to incorporate regional characteristics from the AI design stage at a structural level. The functional problems caused by the Western-centric nature of AI governance are also severe from a technical perspective. For instance, AI trained on Global North data struggles to effectively identify harmful content in African languages or analyze cultural nuances, thus failing to provide locally tailored solutions. Furthermore, the imbalance in digital accessibility has created a perception that technology is developed solely for specific social strata. In Africa, these technical shortcomings go beyond mere inconvenience, making individuals with weak legal protections even more vulnerable. This clearly demonstrates that while AI is rapidly transforming laws, rights, and digital life across Africa, the structural imbalance between law, technology, and society is causing harm. This issue is not confined to the African continent alone. When technology acts as a tool to reproduce and amplify power, neglecting regional contexts or excluding designs for marginalized groups can ultimately exacerbate global technological inequality. The conference proposed actionable measures to address these problems. The core message was the need for immediate and concrete approaches rather than creating entirely new laws. The Complexity of AI Technology Design and Systemic Exclusion First, governance must move closer to the design stage. Dr. Mashinini emphasized that "AI governance must go beyond a reactive approach applied after harm occurs; ethical and legal principles should be embedded from the design phase." She stressed that legal and ethical principles such as accountability, transparency, and rights protection must be inherent in the AI system itself, not merely applied post-harm. This implies that seamless coordination between technology development and regulation is essential. Second, existing legal frameworks must be activated in a coordinated manner. This requires stronger coordination among regulatory bodies, clearer enforcement pathways, and institutional structures capable of responding to technologies that transcend traditional boundaries. Currently, many African countries are approaching AI-related laws individually, making it difficult to establish a consistent governance system. Therefore, a continent-wide coordinated approach is essential. Third, governance must be context-based. Frameworks must reflect the realities of Africa, including linguistic diversity, uneven digital access, and socioeconomic inequalities. Blindly applying uniform governance models developed in the West could exacerbate local conditions. As Dr. Mashinini suggested, AI governance must more deeply reflect local contexts through a 'context-based approach.' This will be a crucial starting point for the collective responsibility of technology regulation. There are many lessons we can learn from the African experience. In particular, for Korean society to successfully establish an AI ethics framework, it must adopt an inclusive approach that considers regional contexts. While Korea is classified as a society with relatively high digital accessibility, it has already experienced instances where rap
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