Translating in the Age of Artificial Intelligence: Professional, Ethical and Intercultural Implications

In the last decade, the field of Machine Translation and Generative AI has evolved with surprising rapidness. This improvement has impacted and continues to impact the translation world, which is undergoing major changes across every sector and needs to adapt to this ongoing revolution. Nowadays, Neural Machine Translation and AI-powered systems are able to generate translation output of high quality, opening translation software opportunities to emerge as a solution to overcome language barriers and reduce time and costs in the language service industry. Nevertheless, this phenomenon is posing huge challenges for translators, who are seeing their work being revolutionised by machines. This thesis aims to provide a review of the latest advancements in Machine Translation and Artificial Intelligence, focusing on the implications of such development on Translators’ work. The present research topic arises from noticing how rapidly the translation field has changed in the last few years, with the emergence of accessible and surprisingly accurate translation tools, and fundamentally attempts to answer one major question: Is Machine Translation replacing human translators? The present work consists of four chapters. The first chapter introduces the topic of Machine Translation by analysing its evolution, from the first research at the beginning of the 20th century to the actual evolution of Neural Machine Translation and Large Language Models. The second chapter deals with the transformation of the translators’ role in the last decade, from a theoretical and practical point of view, highlighting the rise of new professional identities and expertise. The third chapter discusses the ethical challenges that the evolution of Generative AI is proposing, from Data Governance to Education. Ultimately, the fourth chapter, offers insights into the effects of AI on translation in cultural and intercultural contexts, emphasising the importance of human-machine interaction.