Human and Machine Collaboration in Translation: A Systematic Review of Emerging Practices
Abstract
The rapid advancement of Artificial Intelligence (AI) has transformed translation from something primarily done by humans to something done by humans and computers working together to create meaning. This study aims to deeply analyze research on AI-Assisted Translation (AIAT) published from 2020 to 2025 to understand the linguistic, collaborative, and ethical dynamics influencing this profession. Using the PRISMA framework and the CASP checklist, twenty empirical studies were analyzed from the Crossref, Scopus, and Google Scholar databases. The findings revealed three dominant themes: improved linguistic performance thru neural systems and large language models; the emergence of human-AI collaboration reshaping translators' cognitive and professional roles; and ethical concerns regarding bias, transparency, and cultural accountability. These findings indicate that AIAT should not only be understood as a technological innovation, but also as a sociolinguistic phenomenon that requires critical human involvement. This study concludes that effective translation in the digital age relies on the synergy between technological accuracy and human interpretive intelligence
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DOI: https://doi.org/10.31004/jele.v11i1.2093
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