Translation and Teaching in the Economic Field

Daniel Gallego-Hernández

1 Business translation and pedagogy in the age of machine translation

Technological advances in the field of translation have led to the continuous development of machine translation and artificial intelligence. In the field of business translation (Gallego, 2022), these tools have achieved impressive levels of accuracy and speed, making them increasingly attractive not only to clients and professionals, but also to students. This can be inferred from recent studies on machine business translation, such as those by Shih (2013), Alcalde (2016), Peraldi (2016), Läubli et al. (2019), Fischer and Läubli (2020), Liu (2020), Martínez (2022), or Schumacher (2023). These studies have investigated the usefulness of machine translation in financial and business contexts. Their results show that machine translation can be cost-effective and, in some cases, produce translations of comparable or superior quality to human translations. However, the quality of machine translation depends on the system used, and it is important to raise user awareness of the limitations of this technology, emphasizing that the human translator remains crucial in the translation process.

In the case of business translation in the classroom, based on our experience and conversations with colleagues who teach the same specialized translation, it is not untrue that many students are lured by the apparent perfection of the results offered by such systems. The fluency and superficial quality of the translations produced often lead them to place excessive trust in these tools and to neglect essential aspects of technical translation. This lack of attention to detail can result in translations that are grammatically correct but lack conceptual accuracy. This is one of the reasons why it seems necessary to provide machine translation literacy workshops for business translation students (Bowker, 2020).

In our view, this reality poses a series of pedagogical and cognitive challenges in the training of business translators, which few studies on machine business translation, given their current focus, mention but do not elaborate on. Consequently, it is up to the reader, especially those interested in teaching, to find ways to integrate the results of such studies into the teaching of business translation in order to develop effective and productive professional skills, and to emphasize the importance of making students aware of the limitations of this technology and the centrality of the human translator in the translation process.

One of the aspects that seems to be often overlooked in the didactics of business translation is the deep understanding of business issues and the analysis of terminology and its conceptual relationships within and beyond the field. We believe this can help detect semantic-conceptual errors resulting from machine translations. If economic, business, or financial knowledge is neglected in the classroom, students may not be prepared to identify meaning problems or conceptual nuances. Lack of knowledge, combined with excessive confidence in technology, can hinder students from questioning generated translations and deepening their understanding of underlying concepts.