Translation and Interpreting Research

Translation and Interpreting Research

Generative AI and Translation Ethics: A Context-Sensitive Ethical Protocol for Iranian Translators

Document Type : Original Article

Authors
Maryam Vahedi Velashani
Leila Alinouri
Department of Foreign Languages, Isf.C., Islamic Azad University, Isfahan, Iran
10.22054/tir.2026.96650.1103
Abstract
Generative AI in translation raises ethical questions about transparency, accountability, privacy, fairness, and human oversight, yet context-specific guidance, particularly in Iran, is limited. This study examined Iranian translation students’ and professional translators’ perceptions of AI ethics and developed a context-sensitive framework and self-assessment checklist. A single-round, Delphi-informed survey of 45 participants (15 undergraduates, 15 MA students, 15 freelance translators) used a 35-item questionnaire covering six ethical dimensions. Descriptive results showed very high agreement on human-AI collaboration and human accountability, and high agreement on disclosure, transparency, privacy, and fairness. Professionals scored lower than students on several dimensions. Drawing on these findings and an existing six-dimensional model, the study proposes a framework of transparency, accountability, human-AI collaboration, privacy, fairness, and ethical governance. Implications for education, practice, and policy include AI literacy, critical oversight, and flexible disclosure guidelines. The checklist translates these principles into practical questions for responsible AI-assisted translation.
Keywords
Accountability, AI-assisted translation, generative artificial intelligence, human–AI collaboration, Iranian translators, translation ethics