Keywords
machine translation
post-editing
cultural relevance
translation quality
human-AI collaboration
linguistic accuracy
translator education
How to Cite
Abstract
In this study, the role of human post-editing is evaluated as a significant intervention in the process of artificial intelligence-assisted translation. Artificial intelligence (AI) translation technology has greatly impacted the process of multilingual communication through unprecedented speed and processing capacity. Despite these advantages, there are significant limitations and shortcomings on the part of these technologies, such as accuracy and cultural appropriateness. In this regard, the analysis is conducted through contemporary literature on the subject and explores the technological limitations and shortcomings of AI translation technology, the methodologies for post-editing, and the performance and efficacy of AI and human post-editing. The analysis has shown that human post-editing is essential for bridging the gap between technology and culture. A hybrid model is proposed for the most viable solution to the problem.References
1. Al Sammarraie, H. S. M., & Ghassemiazghandi, M. Enhancing Post-Editing Machine Translation Skills Among Iraqi Undergraduate Students. AWEJ for Translation & Literary Studies, 8(2), 2024. – pp. 165–182.
2. Bartaškevičius, O. Light machine translation post-editing effort and quality evaluation of news texts translated from English to Lithuanian (Doctoral dissertation, Kauno technologijos universitetas), 2024. – P. 85.
3. Briva-Iglesias, V. Fostering human-centered, augmented machine translation: Analysing interactive post-editing (Doctoral dissertation, Dublin City University), 2024. – P. 36.
4. Hdidan, A. M. The role and effect of AI in translation. مجلة التربوي, (26), 2025. – pp. 1059–1067.
5. Koka, N. A., & Ahmad, J. Adaptation and attitudes towards technological innovations: Assessing the perceptions of senior lecturers on artificial intelligence (AI) in translation post-editing, 2024. – P. 5.
6. Li, M., & Li, D. Human expertise vs. AI efficiency: A comparative analysis of student and ChatGPT post-editing, 2023. – P. 7.
7. Mbotake, S. G. A post-editing turn in translator education: Towards a creative craftmanship in translation. GPH-International Journal of Social Science and Humanities Research, 7(05), 2024. – pp. 137–170.
8. Mohammed, G. M. S. Exploring the Saudi EFL learners' perceptions and challenges in AI-assisted post-editing tools for writing, 2025. – P. 4.
9. Terribile, S. Productivity in the post-editing of neural machine translation: A mixed-methods analysis of speed and edits at Toppan Digital Language (Doctoral dissertation, The University of Manchester), 2024. – P. 73.
10. Xue-yao, Z. H. A. N. G. A review of research on pre-editing of machine translation. Journal of Literature and Art Studies, 15(1), 2025. – pp. 36–43.