JC Penet, Reader in Translation Industry Studies at Newcastle University, and Joss Moorkens, Associate Professor at DCU, join SlatorPod to talk about the new open-access book Teaching translation in the age of generative AI: New paradigm, new learning?

The duo explains how large language models (LLMs) have a different impact than earlier machine translation breakthroughs as they generate human-like text, respond to prompts, and adapt output to context. 

Public hype around LLMs has affected demand for some translators and fueled misconceptions around the value of studying translation. Although, JC and Joss stress that translation education must adapt.

JC outlines how students need to assess whether output is appropriate for purpose, audience, risk, and context. This places greater importance on skills such as selection, evaluation, and effective prompting, while still relying on core linguistic and cultural competence.

Joss adds that this shift reflects real industry practice, where different content types already receive different levels of automation and human involvement. Drawing on healthcare research, he highlights how AI can outperform traditional workflows in some contexts but fail badly in others, especially across languages with uneven data coverage.

Joss also highlights ethical blind spots that arise when performance metrics dominate decision-making. He describes a “triple bottom line” approach that weighs people, planet, and performance equally.

On fears of de-skilling, JC argues that excluding AI from classrooms poses a greater risk. Without guided engagement, students may use tools uncritically or fail to develop AI literacy altogether. Joss points to initiatives such as LT-LiDER, an Erasmus+ project designed to build AI literacy among educators.

Looking ahead, the duo contends that studying languages and translation remains valuable because it develops deep reading, critical thinking, intercultural awareness, and adaptability.