Use of artificial intelligence tools in the formation of professional competence of future interpreters

Abstract

The purpose of the article is to substantiate the possibilities of using artificial intelligence tools in the formation of professional competence of future interpreters. The methodological basis of the study includes the analysis of scientific sources, synthesis, component-structural analysis, classification, and generalization. The analysis of scientific sources made it possible to determine the current state of the problem in Ukrainian and international scholarly discourse; synthesis enabled the integration of separate approaches to understanding the professional competence of an interpreter; component-structural analysis was used to specify its main components; classification made it possible to identify the areas of application of AI tools in the educational process; and generalization was used to formulate practical recommendations. As a result of the study, the structure of the professional competence of a future interpreter was specified with due regard to the technological factor. It was determined that this competence includes linguistic-communicative, cognitive-operational, intercultural, technological, ethical, and reflective components. It was established that AI tools should be used not as a substitute for interpreting activity, but as means of preparation, training, diagnosis, and reflection. The main areas of their application in the educational process were identified: pre-interpreting preparation, terminology work, modelling of oral communicative situations, training the ability to quickly identify the main message, the use of automatic speech recognition, digital prompts, formative feedback, and ethical regulation of AI use. The article substantiates practical recommendations for improving the professional competence of future interpreters, in particular through independent completion of interpreting tasks before turning to AI, analysis of automatic transcripts, verification of terminological equivalents, training in attention distribution, and the development of rules for academically honest use of digital tools. The results of the study may be useful for translation and interpreting teachers, developers of educational programmes, higher education students, future interpreters, as well as researchers studying the digitalization of translator and interpreter education, methods of teaching interpreting, and pedagogical conditions for the responsible use of artificial intelligence in language education.