PRAGMATIC ERRORS AND ADEQUACY ISSUES IN HUMAN AND AIGENERATED TRANSLATIONS OF ACADEMIC TEXTS (Universal International Scientific Journal, 2026)
The increasing use of artificial intelligence (AI) in academic translation has raisedimportant questions about translation quality beyond grammatical accuracy and lexical fluency. Inparticular, the pragmatic dimension of translation, which involves the preservation of context-dependentmeaning, authorial stance, and discourse conventions, remains underexplored in comparative humanand AI translation research. This study investigates pragmatic errors and their impact on translationaladequacy in human and AI-generated translations of academic texts. Adopting a qualitativelinguopragmatic approach, the study analyses a corpus of academic research article abstracts translatedby human translators and an AI-based translation system. The analysis focuses on key pragmaticfeatures, including implicature, hedging and stance, deixis, and register and discourse organisation. Thefindings reveal systematic differences between human and AI-generated translations. While AIgenerated translations demonstrate high levels of formal fluency, they exhibit recurrent pragmaticweaknesses, such as over-explicitation, inappropriate stance calibration, and discourse-levelmisalignment, which cumulatively reduce translational adequacy in academic contexts. Humantranslations, although not free from pragmatic deviation, show greater sensitivity to communicativeintent and academic discourse norms through context-aware and strategic decision-making. The studycontributes to translation quality assessment by highlighting pragmatic errors as a crucial indicator ofadequacy and underscores the continued importance of pragmatic competence in AI-assisted academictranslation and translator education.
Keywords: pragmatic errors; translational adequacy; AI-generated translation