Abstract
Problem Statement. The advent of neural network-based machine translation systems and large language models has brought significant changes to the translation services market, impacting employment and prompting concerns among students and prospective linguists about the future of the translation profession. This study aims to identify mismatches between the expectations of linguistics students and the real-life market situation to promote more realistic attitudes in students, and increase their motivation.Materials and Methods. In 2024, a survey was conducted among 122 Linguistics majors from four Russian universities. The sample was representative, with a reliability level of 66.7 %. The survey included questions regarding preferred types of translation types in demand, and the outlook for the profession, facilitating a comparative analysis with the current situation on the translation services market.Results and Discussion. While students have a reasonable understanding of market demand for various types of translation, their preferences do not align with the most in-demand industries. Notably, there is a low level of interest in scientific, technical, medical, and legal translation, despite these fields being highly sought after. Moreover, many students hold a pessimistic view of the profession's future, fearing that translators will be replaced by machine translation systems.Conclusions. Despite their awareness of market realities, students are reluctant to focus on the most in-demand types of translation. This reluctance is attributed to a lack of knowledge in the exact sciences and a distorted perception of the profession, influenced by popular culture. The study recommends strengthening career guidance efforts and modernizing educational programs to better align with market needs, as well as emphasizing the continued importance of professional translators in the context of technological advancements
Published Version
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