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The rise of AI-powered language technologies, exemplified by products like DeepL and ChatGPT, has propelled the advancements towards widespread acceptance, integrating them into daily communication and professional routines. This transformation holds significant implications for social interactions and knowledge dissemination. However, the dominance of these technologies poses challenges, particularly for non-native English speakers. This dominance not only limits information access for non-native English speakers but also risks fostering a monocultural AI primarily proficient in English, neglecting other languages and cultures. Nonetheless, the revolutionary benefits of AI advancement may disproportionately benefit English native speakers unless corrective measures are taken. The present study aims to offer a thorough review of the advancements, focusing specifically on the fields of education and healthcare. These two sectors have been significantly impacted by these improvements, and the study seeks to provide a detailed analysis of the changes and developments within them. To address this inequality, sourcing language training data from diverse linguistic backgrounds and implementing localization strategies are proposed as solutions. Additionally, collaboration between scientists and linguists can enhance the linguistic and cultural sensitivity of AI language models. Furthermore, introducing an artificial language into AI chatbot systems could mitigate inequality by enhancing accessibility and comprehension for non-native English speakers, thereby promoting inclusivity.
Sunyoung Park (Fri,) studied this question.