Human vs. ChatGPT Translation: Comparative Analysis of Accuracy, Fluency, and Cultural Adaptation

Abstract

The rapid development of artificial intelligence has significantly transformed translation practices, creating new opportunities and challenges for professional translators, researchers, and language learners. ChatGPT, as a generative artificial intelligence system, can produce translations that are grammatically correct, contextually appropriate, and stylistically coherent. However, its performance must be evaluated in relation to human translation, particularly regarding semantic accuracy, linguistic fluency, and cultural adaptation. This study aims to compare human and ChatGPT translation through a qualitative analytical framework focusing on these three dimensions. The research draws on established approaches to translation quality assessment, functional translation theory, and machine translation evaluation. It examines how human translators and ChatGPT may differ in interpreting contextual meaning, reproducing stylistic features, and transferring culture-specific expressions. The analysis suggests that ChatGPT can offer considerable advantages in speed, consistency, and the production of fluent target-language texts. Human translators, however, retain important advantages in culturally sensitive interpretation, pragmatic judgment, creative adaptation, and the resolution of complex contextual ambiguities. The study argues that translation quality cannot be measured exclusively through grammatical correctness or lexical equivalence. Instead, it requires an integrated assessment of meaning, communicative purpose, target-audience expectations, and cultural appropriateness. A complementary human–AI translation model is proposed as a practical approach to improving translation quality while maintaining human responsibility for the final text.