Fostering critical reflection on GenAI in translation practice

The rapid integration of generative AI into translation and language assessment raises critical questions about its ethical implications and practical challenges. This study, drawing from a semester-long module within the MA Translation and Professional Communication Skills programme, showcases a teaching practice that incorporates AI use in translation while foregrounding ethical considerations before students engage with these tools. By designing diverse teaching activities and assessments, the program fosters critical reflection and ethical awareness of AI’s role in translation practice. Students engaged in a series of assignments aimed at analysing the effectiveness and limitations of AI tools in professional translation contexts, specifically exploring AI's capacity to handle complex cultural references, biases, and contextual nuances.<br/><br/>Throughout the course, students reflected on topics such as the ethical considerations surrounding Computer-Assisted Translation (CAT) tools, the role of human translators in an AI-driven future, and the challenges of translating cultural nuances. In classroom discussions, they examined issues like gender and racial bias, training data inequalities, and intellectual property rights, all of which present significant ethical considerations in AI use for translation. The study also highlights examples from students’ work, illustrating how generative AI struggles with idiomatic and culturally loaded expressions, often leading to unidiomatic or inaccurate translations without human intervention.<br/><br/>This study contributes to the discourse on ethical AI in language practice by providing insights into student perspectives on AI in translation, revealing a strong preference for a collaborative approach where human expertise and AI complement each other. The findings advocate for a curriculum that encourages critical analysis of AI, equipping future translators with the skills to navigate the ethical complexities of AI-enhanced translation and assessment.