Legal terminology translation: humans vs algorithms

Abstract

The translation of legal terminology represents one of the most challenging areas of specialized translation, requiring not only linguistic competence but also deep understanding of legal systems, cultural nuances, and the intended legal effect of documents. Within the fast advancement of Neural Machine Translation (NMT) and Large Language Models (LLMs), the question arises: can algorithms replace human legal translators? This article examines the complexities of legal language, compares human and machine translation approaches, identifies the strengths and weaknesses of each, and proposes a hybrid model as the most effective solution for legal translation in the contemporary digital landscape. The article argues that while algorithms excel at speed and consistency, only human translators possess the semantic, pragmatic, and juridical competence necessary to ensure absolute precision in legal documents.