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Preserving Linguistic Diversity and Cultural Authenticity in NLP-Based Systems Like ChatGPT
The disparity between Arabic Natural Language Processing (NLP) and English NLP is poised to exert a substantial influence on the emerging knowledge structures shaped by ChatGPT. As the dominant medium, culture, and form, English is likely to impose modeling rules on Arabic NLP. This raises concerns about the preservation and vitality of languages such as Arabic, Persian, and Urdu in the face of the epistemic configuration unleashed by ChatGPT. The paradigm shift in education triggered by ChatGPT further accentuates these concerns. Students increasingly rely on the system for their studies, including producing complete papers. In Middle Eastern studies and other humanities, this reliance often leads to the creation of artificial scholarship based on English translations of non-English source materials and topics. Consequently, the substance and authenticity of scholarship are compromised, potentially shaping the future foundations of knowledge in the Arabic-speaking world around an inherently different, English-based system. The implications of this trend are significant. It raises questions about preserving linguistic diversity, cultural authenticity, and the equitable representation of knowledge systems, particularly in natural language-based systems. How can we ensure that the epistemic configurations facilitated by ChatGPT do not overshadow or diminish the inherent value of languages like Arabic, Persian, and Urdu in constructing knowledge and preserving cultural heritage? How do we bridge the gap between non-English NLP systems and English NLP? These are some of the concerns that I will explore in my presentation.
Geographic Area
Islamic World
Sub Area