The Reconstruction of Translation Competence in the Digital Intelligence Era and Its Implications for the MTI Education in China

Abstract

This paper examines the profound impact of the Digital Intelligence Era, marked by artificial intelligence and neural machine translation, on the foundational concept of translation competence. It argues that traditional models, while empirically robust, are premised on a paradigm of human-centric cognition with technology as an assistive tool. In response, the study proposes a comprehensive reconstruction towards a Human-Machine Collaborative Competence (HMCC) framework. This new model redefines the translator as a “Language Service Architect”, whose core meta-competence is the strategic orchestration of human and artificial intelligence. The HMCC framework is elaborated across four integrated dimensions: Strategic Decision-Making, Technological & Data Literacy, Bilingual-Cultural Proficiency, and Domain & Project Management. We then propose a systemic transformation encompassing redefined program objectives, a restructured curriculum centered on a core technology cluster and “Translation of China” practice, and innovative pedagogy based on a “Classroom-Platform-Project” ecosystem. The analysis acknowledges significant implementation challenges, including techno-ethical dilemmas, faculty readiness, and lagging assessment systems. Ultimately, it posits that successfully cultivating the HMCC—with sophisticated post-editing and cultural finalization as its exemplar—is essential for building China’s national translation capacity and ensuring its voice in global digital discourse.