The Evolving Role of Human Translators in the Age of Artificial Intelligence: Perceptions, Challenges, and Adaptation Strategies

Abstract

The rise of artificial intelligence (AI) in translation has drastically altered the profession, with machine translation (MT) and neural machine translation (NMT) introducing automation and efficiency. While AI brings benefits such as increased productivity and cost reduction, it raises significant concerns among translators regarding job displacement, ethical risks, and the devaluation of human translation. This study aims to explore the perceptions of translators, educators, and students about the impact of AI on their translation profession, addressing concerns and suggesting strategies for adapting to the AI-driven landscape. Using a qualitative method (semi-structured interviews), the research gathered insights into how translators perceive the evolving nature of their roles, the challenges they face, and their recommendations for skill development and adaptation. Findings indicate that AI has enhanced efficiency in translation work, particularly in technical, legal, and research-based translations, shifting translators’ roles toward editing and post-editing AI-generated drafts. Tools like MemoQWeb help maintain consistency through translation memories and term bases. However, AI struggles with literary and cultural translations due to figurative language and cultural nuances, and ethical concerns such as data privacy and translator deskilling remain pressing. Translators emphasize the need for skill development in AI-assisted workflows to balance automation with human expertise. This study contributes to the growing discourse on AI in translation by providing empirical insights into how translators navigate AI-driven changes, the skills required for adaptation, and the ethical challenges they face. It highlights the importance of integrating AI literacy into translator education and professional development, offering strategies for leveraging AI while preserving human creativity and linguistic accuracy.