Teaching subtitling in the times of generative AI

This chapter explores the integration of Generative Artificial Intelligence (GenAI) into subtitler training and its impact on translator education. Drawing on teaching experiences and research insights, it presents strategies for designing and delivering training courses that prepare future subtitling professionals to work effectively in an AI-enhanced industry. Subtitling is a multifaceted translation practice that requires technical, linguistic and cultural skills. Recent developments in GenAI are reshaping how these skills are taught and applied. Based on realistic scenarios and exploratory teaching methods, the chapter examines how Large Language Models (LLMs) can support different stages of the subtitling process through inquisitive integration. The discussion encompasses practical approaches to integrating GenAI tools into the classroom, drawing on examples related to the translation of cultural references and template creation. The chapter adopts a hands-on problem-solving approach to training that encourages students to evaluate technological possibilities whilst developing foundational knowledge. Through examples from teaching practice, it shows how comparing different AI solutions and assessing their suitability for specific tasks helps students make informed decisions about implementing automated solutions. This approach positions students as active agents in their learning process while helping them understand the potential and limitations of automation. Critically examining the role of educators in this changing landscape, the chapter advocates for training that prepares adaptable professionals who can navigate technological developments whilst maintaining high standards and advocating for sustainable working conditions. More broadly, it contributes to discussions about providing students with the necessary tools and knowledge to shape sustainable careers in an increasingly automated media localisation industry.