Human and Artificial Intelligence in Literary Translation Evaluating Meaning, Style, and Cultural Representation

Abstract

The development of artificial intelligence in translation raises questions about its ability to maintain meaning, style, and cultural representation in English literature. This study aims to compare human and AI translations in parts of texts that contain metaphors, idioms, narrative styles, and cultural elements. The study used a comparative qualitative approach by involving three human translators, one AI model, and two translation experts as validators. Data was collected through translation documentation and expert review, then analyzed using comparative textual analysis and thematic coding. The results show that human translators more consistently retain figurative nuances, narrative voices, and cultural distinctiveness, while AI tends to produce more explicit and standardized translations. The findings confirm the importance of human interpretation in AI-assisted literary translation