| Abstract: |
The rapid advancement of Artificial Intelligence (AI) has significantly transformed the field of scientific
and technical (sci-tech) translation, offering promising tools for increased efficiency and accessibility.
However, its application in low-resource languages such as Igbo, particularly in specialized domains like
medicine, are fraught with challenges. This paper critically examines the limitations of AI in English-Igbo
translation of medical texts. By analyzing selected AI-generated translations and comparing them with
human translations, the study identifies key semantic, syntactic, and terminological discrepancies that
hinder accurate meaning transfer. It also explores the cultural and linguistic complexities that AI often
overlooks due to the limited linguistic datasets available in Igbo. The analysis reveals that while AI
demonstrates potential in bridging linguistic gaps, its current performance in English-Igbo sci-tech
translation is inadequate for high-stakes contexts like medicine, where precision is paramount. The paper
advocates for collaborative human-AI models and the urgent need for localized corpora development to
enhance AI translation efficacy in indigenous African languages. |
EBONYI JOURNAL OF LANGUAGE
