GenAI for self-directed individual and collaborative learning in the training of conference interpreters for the European Union institutions

Abstract

Students pursuing studies in conference interpreting with a view to taking the European Union’s interinstitutional accreditation test are generally required to invest in self-directed individual and collaborative learning to complement their in-class training. Digital technologies may prove beneficial in this regard. The present paper discusses the four main digital technologies in the interpreting workflow, viz., computer-assisted interpreting training (CAIT) tools, computer-assisted or computer-aided interpreting (CAI) tools, remote or distance interpreting, and machine interpreting. While there may be some overlap, generative AI (GenAI) is proposed as a fifth, distinct category. Four piloted GenAI-based proposals are put forward to complement in-class training, along with their learning outcomes and suggested assessment method. In addition, the importance of critical AI literacy is addressed as a key skill for both trainers and students in preparing for institutional interpretation in the 21st century. Finally, the paper presents the results of a small-scale survey among students, gauging their experiences using GenAI for individual and collaborative tasks in the framework of a postgraduate program training students for the EU’s interinstitutional accreditation test. While limited in size and scope, the survey provides insight into student engagement with this new technology and supports further curriculum refinement.