Subtitling English Legal Acronyms into Arabic: Human vs Machine
https://doi.org/10.17803/2713-0533.2024.4.30.810-842
Abstract
The development of artificial intelligence (AI) and machine translation (MT) technologies made the process of translation easier. The study examines the translation strategies used by Netflix, Google Translate (GT), ChatGPT (GPT), and Gemini (GEM) to render 30 English legal acronyms into Arabic. Adopting the taxonomy suggested by Al-Hamly and Farghal to translate reduced forms, the analysis showed that every translator (human, MT, and AI) uses different strategies to render the acronyms into Arabic. The findings showed that the majority of the English legal acronyms were unpacked and translated literally “Translation Alone Unpacking.” GPT employed this strategy the most at 50 %, followed by Netflix and GT at 26.6 % each and GEM at 13.3 %. The second most frequently used translation strategy is “Cultural Substitution” that was utilized by Netflix (40 %), followed by GPT (23.3 %), and GEM and GT at 16.6 % each. The analysis showed that GT has more cases of mistranslation than the other investigated systems. The study concludes that artificial intelligence tools have advanced significantly and are now almost as good as humans. Therefore, when translating legal acronyms, combining machine translation with human intervention will likely improve accuracy and cultural sensitivity while saving time, cost, and effort.
About the Authors
A. S. Haider
Applied Science Private University
Jordan
Jordan
Ahmad S. Haider, PhD (Linguistics), Associate Professor, Department of the English Language and Translation
Amman
R. Alkhatib
Applied Science Private University
Jordan
Jordan
Ruba Alkhatib, MA (Audio-Visual and Mass Media Translation)
Amman
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For citations:
Haider A.S., Alkhatib R. Subtitling English Legal Acronyms into Arabic: Human vs Machine. Kutafin Law Review. 2024;11(4):810. https://doi.org/10.17803/2713-0533.2024.4.30.810-842
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