Challenges And Strategies Of Translating Scientific Texts: A Comparative Study Of Human Translation And Artificial Intelligence

Abstract

 The advent of Artificial Intelligence (AI) has markedly influenced the field of translation, particularly within the scientific community. The study aims to explore the challenges faced by human translators and AI apps highlighting the strategies they use when translating scientific texts from English into Arabic and vice versa. It also seeks to compare the translations produced by human translators with those generated by Artificial Intelligence. Moreover, this study endeavors to identify potential solutions for enhancing translation efficiency and productivity, particularly in the domain of scientific translation. The author adopted an analytical-descriptive methodology and a comparative analysis of the translations produced. To achieve this, a comprehensive test comprising six texts, including (18) collocations, phrasal verbs and abbreviations was administered to assess (20) Arab translators’ performance and challenges encountered. The same test was inputted to (10) AI applications to compare ultimately the performance of both human translators and AI tools efficiency in translating scientific texts. The outcomes were analysed and evaluated with the assistance of three professional translators in addition to slandered translation. The research’s findings aim to advance translation efficiency and productivity, especially within the scientific translation domain, which is pivotal for international knowledge and collaboration. The data analysis was carried out according to Ghazala's classification (2008) for the challenges, Newmark's taxonomy (1980) for strategies, and Prieto's criteria (2015) for the assessment of the translations of translators and AI.