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Artificial Intelligence (AI), particularly large language models such as ChatGPT, is reshaping translation practices and redefining translator training. While AI has dramatically enhanced translation speed, efficiency, and cost-effectiveness, its impact on translation students’ training practices remains underexplored. Hence, this study examines how AI technology, specifically ChatGPT translator, influences translation practices and the role of translators in computer-aided translation (CAT). The goal is twofold: (1) to determine if there is a relationship between translation students’ choices and their assessment of AI-generated translations (ChatGPT-T), considering their language proficiency and professional status; and (2) to investigate whether professional human translations (HT) can be accurately distinguished from AI outputs through linguistic analysis alone. Eight advanced translation students participated in the study, evaluating ChatGPT-T and HT outputs of both technical and literary texts translated from German into Arabic and English. The analysis incorporated both qualitative assessments—based on participants’ observations and annotations—and quantitative evaluation using the BiLingual Evaluation Understudy (BLEU) score to measure AI translation quality. Findings indicate that language proficiency and professional experience significantly affect evaluators’ judgments of AI translations. While students with higher proficiency and professional training more accurately distinguished HT from ChatGPT-T—particularly in stylistically complex literary texts—AI outputs were competitive in technical domains, often perceived as near-human. However, linguistic analysis alone proved insufficient for perfect discrimination between AI and HT, underscoring the need to apply broader criteria, including cultural and stylistic sensitivity in translation evaluation. Ultimately, the study highlights that AI serves as a powerful yet complementary tool, supporting rather than replacing human translators. Its integration into training can enhance the development of key competencies, foster efficiency, and prepare future translators to meet evolving industry demands through effective collaboration between human intelligence and AI technologies.
Muneera Muftah (Wed,) studied this question.