The effect of using AI and Google Translate on translating BBC media texts into Arabic

Recent post-human translation studies increasingly explore the intricate relationship between artificial intelligence (AI) and translation. This paper examines the complexities of AI, with a focus on machine translation (MT), and its transformative effect on translation in light of technological advancements. Such transformation has led to new roles and skills for translators. Our research primarily scrutinizes the style and messaging quality of English-Arabic media text translations. We aim to illuminate how AI and MT challenge the translation industry, discussing both potential benefits and risks for language professionals, and presenting a theoretical framework for the changing roles of human translators. This study specifically identifies common errors in MT for Arabic-English news texts and vice versa, assessing translation quality, fluency, semantic accuracy, and the need for human intervention in corrections. We selected purposeful examples from online newspapers and used a qualitative method for data analysis, identifying errors based on Hsu's (2014) machine translation error classification.