Time to Edit: Machine Translation in Modern Digital Culture (Education and Science)

Abstract

Rapid advances in machine translation systems, digital communication technologies in general, and artificial intelligence significantly reduce the amount of work required to produce intellectual products, but they do not relieve humans of responsibility for the results created with their help. Time to edit, a popular expression in digital culture, is becoming increasingly relevant today in any field of activity involving work with digital systems. This article examines some of the limitations of modern (neural) translation systems that create specific situations for post-editing. Conclusions are drawn on the basis of a comparison of algorithms of lexical and morphological analysis in traditional and modern (neural) translation systems, as well as on the basis of testing such systems when working with new terminology. The article emphasises the relevance of working with machine translation systems and the need for training in post-editing, both in creating scientific and educational products, as well as in professional language and translation training.