HUMAN–AI COLLABORATION IN TRANSLATION: THE RISE OF THE POST-EDITING PARADIGM
Keywords:
artificial intelligence, neural machine translation, post-editing, human-AI collaboration, hybrid translation workflow, translator competence, translation quality.Abstract
This thesis examines the transformation of the translator’s professional role in the age of artificial intelligence (AI). It argues that neural machine translation does not render human translators obsolete but reorganises their work around a collaborative, post-editing paradigm. Through a conceptual review of recent developments in machine translation and translation studies, the study describes the hybrid workflow in which AI generates a rapid draft while the human translator ensures meaning, style, terminology, cultural appropriateness and ethical acceptability. It identifies the new competencies — post-editing, AI-tool literacy, terminology management and ethical awareness — that define the modern translator, and concludes that the most productive future of translation lies in cooperation rather than competition between human and machine.
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