Intercultural Interfaces: Artificial intelligence and the challenges of cultural sensitivity

This study investigates the intersection of cultural sensitivity and AI-driven machine translation tools in translation education, with a focus on Portuguese-Chinese language pairs. Drawing on mixed-methods research, it explores how students perceive and use AI tools for translation, the challenges they face, and the tools’ limitations in managing cultural nuances, idiomatic expressions, and contextually rich texts. Findings highlight that while tools like DeepL and ChatGPT offer efficiency and accessibility, they often fail to capture cultural and emotional depth, necessitating human oversight. Higher-performing students critically engage with AI outputs, while less proficient students rely heavily on these tools, often overlooking errors. The study underscores the need for translation curricula to integrate AI literacy, critical thinking, and cultural analysis to prepare students for hybrid human-AI workflows. This research contributes to a deeper understanding of AI’s role in culturally sensitive translation and its pedagogical implications.