في الترجمة
Volume 13, Numéro 1, Pages 186-207
2026-05-31

Ai-assisted Revision In Safety-critical Translation: A Corpus-based Analysis Of Aviation Maintenance Instructions



Authors : Remichi Selwa .

Abstract

The integration of artificial intelligence (AI) into translation workflows is transforming professional translation practices, particularly in technical and safety-critical domains. This study examines the role of AI-assisted revision in improving error detection in machine-translated safety documentation.Using a small corpus of aviation maintenance instructions translated from English into French, the research compares two revision workflows: traditional human revision and AI-assisted revision. Translation errors in the machine translation output were analyzed using a structured error taxonomy covering terminology errors, meaning distortions, procedural sequence errors, numerical inaccuracies, and omissions. The results indicate that AI-assisted revision achieved a higher error detection rate than traditional human revision, particularly for terminology inconsistencies and numerical anomalies. However, the findings also confirm that human expertise remains essential for interpreting contextual meaning and identifying pragmatic ambiguities. The study highlights the potential of hybrid human–AI revision models as effective quality assurance mechanisms for safety-critical technical communication.

Keywords

Artificial Intelligence (AI) ; AI-assisted revision ; safety-critical translation ; error detection ; translation quality assurance

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