PRAGMATIC EFFECT RECONSTRUCTION STRATEGIES IN ENGLISH- UZBEK LITERARY TRANSLATION: A COMPARATIVE STUDY OF GENERATIVE AI AND HUMAN TRANSLATION

Abstract

This article examines pragmatic effect reconstruction strategies in English-Uzbek literary translation through a comparative analysis of generative artificial intelligence and human translation approaches. The study aims to identify the ways in which pragmatic meanings, emotional-expressive features, cultural implications, and authorial intentions are preserved and reconstructed in the process of literary translation. Particular attention is given to the differences between AI- generated translations and human translations in terms of contextual interpretation, stylistic adaptation, cultural equivalence, and the reproduction of the reader’s emotional response. The research employs comparative, descriptive, contextual, and analytical methods to examine selected literary texts translated from English into Uzbek. The study analyzes the effectiveness of generative AI tools in recognizing linguistic patterns, maintaining semantic accuracy, and producing stylistically acceptable translations, while also evaluating the role of human translators in interpreting implicit meanings, cultural references, metaphors, and pragmatic intentions. The findings indicate that generative AI demonstrates significant potential in ensuring lexical and structural accuracy; however, human translation remains essential for reconstructing complex pragmatic effects, cultural nuances, and artistic expressiveness. The article concludes that an effective approach to contemporary literary translation requires the integration of generative AI capabilities with human interpretative expertise. Such a hybrid model can contribute to improving translation quality by combining technological efficiency with cultural and pragmatic sensitivity.