AI-Driven Technologies: Challenges and Countermeasures of Machine Translation in ELF Contexts
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With the revolution and development in artificial intelligence (AI) and translation amongst ELF learners, the accuracy and quality of machine translation (MT) has facilitated the process of language translations. This article discusses the challenges and countermeasures related with AI-driven machine translation (MT) technologies and the uses in the context of English as a global lingua franca (ELF) where MT and AI have significant roles in terms of a tool to express certain language output. However, the integration of these technologies in the setting, particularly in academic contexts, reveals several challenges. Key issues including linguistic inaccuracies, cultural insensitivity, and domain-specific translation difficulties have been criticized. Moreover, this paper shows a range of countermeasures, such as, hybrid translation models that combine AI with human expertise, the development of domain-specific translation tools, and the implementation of human expertise guidelines. Also, the paper highlights the importance of interdisciplinary of using machine translation and continuous improvement in AI technologies to enhance translation quality.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
* กองบรรณาธิการทรงไว้ซึ่งสิทธิในการพิจารณาและตัดสินการลงตีพิมพ์ในวารสาร
** ทัศนะและข้อคิดเห็นที่ปรากฎในบทความต่าง ๆ ของวารสารเป็นของผู้เขียน มิใช่ความคิดเห็นของกองบรรณาธิการ
และมิใช่ความรับผิดชอบของคณะมนุษยศาสตร์และสังคมศาสตร์ มหาวิทยาลัยวิทยาลัยราชภัฏเชียงใหม่
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