Computer-assisted language mediation in teaching human-centred augmented translation

In the evolving landscape of translation education, the integration of computer-assisted language mediation has emerged as a key strategy for teaching human-centred augmented translation. This study explores the implementation of generative AI (GenAI) models, in particular Large Language Models (LLMs), in translation workflows to enhance translator competence while maintaining ethical standards. Using custom AI systems that adapt and evolve with new translations, students can be trained to critically evaluate AI-generated content and manage hybrid translation workflows that combine AI output with human expertise. The research emphasises the importance of understanding the limitations and potential biases of AI, and advocates a balanced approach in which AI augments rather than replaces human judgement. Practical examples and exercises demonstrate the strengths and weaknesses of using AI in information processing and multilingual text generation, with the ultimate aim of training a new generation of translators to use AI technologies responsibly.