Integrating professional machine translation literacy and data literacy

Abstract The data-driven paradigm of neural machine translation is a powerful translation technology based on state-of-the art approaches in artificial intelligence research. This technology is employed extensively in the professional translation process, requiring an adequate degree of machine translation literacy on the part of professional translators. At the same time, the increasing datafication to be observed in modern society – both in private as well as in professional contexts – contributes to the rise in prominence of another digital literacy, i. e., data literacy, which is also of high relevance with regard to data-driven machine translation. The present paper analyses and discusses in detail the individual dimensions and subdimensions of professional machine translation literacy and data literacy and attempts to integrate the two concepts. It thereby lays the theoretical foundation for a didactic project concerned with teaching data literacy in its machine translation-specific form to students in the fields of translation and specialised communication studies.