2024, Vol.25, No.3

The Journal of Translation Studies 2023 KCI Impact Factor : 1.49

pISSN : 1229-795X
https://journal.kci.go.kr/kats

The rapid advancement of artificial intelligence (AI) is poised to revolutionize various fields of expertise, including translation. This essay explores the evolution of the translation ecosystem in the age of AI, focusing on five key areas. First, I introduce the term Tower of Babel 3.0 to describe the potential impact of GenAI on the public’s perception of translation. Second, I discuss the implications of technological advancements for educators and practitioners in the field of translation. I suggest the notion of translational singularity, which signifies a transformative threshold where AI overtakes human intelligence in every facet of translation. Third, I investigate the hyper-agency of machine translators, a term that denotes their growing dominance and autonomy in the translation industry. This shift in the status of machines raises several concerns, including ethical dilemmas and the potential displacement of human translators. Fourth, I extend John Searle’s “Chinese Room” metaphor to the present context, highlighting the rise of translators with limited proficiency in the target language. This metaphor is used to critically assess the essence of studying and performing translation. Finally, I examine the changing roles of human translators in an AI-driven world, focusing on how their responsibilities and skill sets may diverge from traditional expectations.

The emergence of generative AI has introduced new challenges in translator training. Through in-depth interviews of eight translator trainers, this study aims to explore the changes experienced by graduate-level translator trainers in the AI era, how they are adapting to these developments, and their perspectives on translation competence, trainees’ use of AI for their translation and the future direction of translator training. The study first examines major translation competence models along with their relevance to graduate-level translator training and reviews recent trends in research on neural machine translation-based post-editing. It then discusses the latest trends in machine translation research, questioning the traditional dichotomy between human and machine translation. Additionally, the study introduces the concepts of augmented translation and machine translation literacy, exploring their possible educational applications. The study finds that the trainers were opposed to trainees’ use of AI in translation on the grounds that it will hinder the development of translation competence. They were also found to be skeptical about the relevance of translation competence models, as well as machine translation post-editing, to graduate-level translator training. The findings suggest that it is the trainers themselves, rather than the trainees, who need education on machine translation literacy. The paper concludes by discussing the implications of the interview findings for graduate-level translator training and translation studies.

In response to the growing trend of creatively adapting Korean novel titles, this study evaluates ChatGPT's ability to rewrite titles in a creative manner, rather than resorting to literal translation. The AI was tasked with analyzing the plots and themes of four Korean novels and generating English titles that captured both their central themes and original intent. A comparative analysis was then conducted between these AI-generated titles and those produced by professional literary translators, focusing on functional similarities and differences. The findings revealed that the human translators incorporated a broader range of functions in their adaptations, while ChatGPT produced titles with a more limited functional scope. Despite its limitations in producing nuanced titles, ChatGPT can nonetheless serve as a cognitive tool to assist human translators in crafting more innovative and functionally appropriate titles.