Document Type : Research Paper
Authors
1 Assistant Professor of English Language and Literature, Faculty of Literature and Humanities, Hakim Sabzevari University, Sabzevar, Iran
2 Adjunct Lecturer in English Language and Literature, Department of English Language and Literature, Faculty of Literature and Humanities, Hakim Sabzevari University, Sabzevar, Iran.
3 Ph.D. Student of TEFL, Faculty of Literature and Humanities, Hakim Sabzevari University, Sabzevar, Iran
Abstract
Against the backdrop of rapid advances in artificial intelligence, this qualitative study examines how professional translators perceive the benefits, challenges, and likely future trajectories of AI-assisted translation. Semi-structured interviews were conducted via videoconferencing platforms with twenty translators—each with at least three years of experience—drawn from diverse specializations and work settings. Interviews were transcribed verbatim and analyzed thematically following Braun and Clarke’s guidelines; to enhance credibility, the coding was reviewed by an experienced colleague. The findings highlight four salient advantages: (1) increased speed through drafting and automation of repetitive segments; (2) cost-effectiveness for large projects or under tight deadlines; (3) improved consistency and tighter terminological control, especially in technical texts; and (4) facilitation of collaboration via shared translation memories and glossaries. Alongside these gains, participants reported notable risks and challenges, including persistent difficulties in representing cultural and pragmatic nuance or achieving rhetorical effect; the danger of over-reliance that may erode skills and inflate client expectations; fatigue associated with post-editing unfamiliar or ambiguous outputs; ethical concerns regarding data privacy, confidentiality, authorship, and job security; and technical limitations in low-resource languages or complex language varieties. Synthesizing convergent and divergent evidence, the study proposes a “human-in-the-loop” model oriented toward personalization and productivity, in which AI functions as an assistant within a human-centered educational and professional scaffold, while human expertise remains decisive for problem formulation, audience adaptation, quality assurance, and value-laden judgment. Practical implications include targeted professional development in AI literacy, post-editing strategies, and bias awareness; the redesign of translator-training curricula to cultivate hybrid competencies and critical appraisal of AI outputs; and the articulation of organizational and sectoral policies on data governance, transparency, and fair remuneration. Overall, the results caution against both techno-pessimism and uncritical hype, and instead advocate for judicious human–AI collaboration that deploys AI where it adds value while safeguarding the cultural depth, ethical integrity, and creative agency of professional translators.
Keywords
- AI-Assisted Translation
- Professional Translators
- Generative/Neural MT
- Post-editing
- Human–AI Collaboration
- Ethics
Main Subjects
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