Book Review: Joss Moorkens, Andy Way, and Séamus Lankford. Automating Translation. London and New York: Routledge, 2025. 248 pp

Despite the utopian and dystopian visions of the translator’s position in the light of AI, it would be no understatement to claim that the rapid integration of machine translation (MT) and generative artificial intelligence into the language industry, noted as “digital paradigm”(Gambier, 2016) or “technological turn” (Jiménez-Crespo, 2020), has irrevocably altered the landscape of translation practice, pedagogy, and research. Even in the 2016 Translation Technology Landscape Report, the Translation Automation User Society (TAUS) has predicted “fully automatic useful translation” during the next twenty years or so (Massardo, van der Meer & Khalilov, 2016). Automating Translation, authored by leading experts Joss Moorkens, Andy Way, and Séamus Lankford, arrives at a critical juncture to provide a comprehensive, balanced, and deeply insightful guide to these transformative technologies. Far from being a mere technical manual, this volume masterfully demystifies the core principles of neural machine translation (NMT) and large language models (LLMs) while embedding them within a robust sociotechnical and ethical framework. It successfully bridges the often-daunting gap between theoretical abstraction and practical application, empowering readers—from students to seasoned professionals—to not only understand but also critically engage with and even build contemporary translation systems.