Facing innovation

Knowledge-driven vs. tech-driven translation training

Translation schools should be the workshop where wordsmiths forge new translation professionals through the masterly combination of theory and practice. Translation teachers should ideally align the conclusions of translation studies to the professional needs of the translation industry through thorough analyses and experimental research.

A widespread agreement exists within the translation industry that translators must specialize, focusing on specific subject areas to meet the customers’ demand. Unfortunately, the fast pace of technological innovation and the rapid growth of information and knowledge are re-shaping the nature and meaning of specialization. There are so many new subjects to know and there is much more to know about each of them that no translator can be expected to have the knowledge required to translate all types of documents well and within a reasonable amount of time.

On the other side, productivity has been the mantra of the translation industry since the introduction of terminology and translation memory management systems in the earliest 1990’s. A quarter of a century after the introduction of the technological innovations that radically changed the translation industry, datafication is the corner stone in technology evolution.

As Samuel Johnson reportedly said, “knowledge is of two kinds. We know a subject ourselves, or we know where we can find information upon it.”

Up to forty years ago, skills came from knowledge; since a decade or two, abilities have been dominating knowledge. Today, not only is expert knowledge in a given subject very important, technological skills are becoming increasingly relevant to be capable of accessing the appropriate resources.

All this makes translation competence a combination of data, tools, and knowledge: it is less and less a question of language knowledge and more one of knowing how to use it and the right tools to exploit it.

In 1987, the American economist Robert Solow earned a Nobel Prize for showing that economic growth does not come from people working harder, but from working smarter, by getting more from less, and in the process freeing up time to do other things impossible beforehand.

This should definitely be the paradigm for the last generation of translators, but translation scholars, teachers, and professionals have seemingly been failing to implement it.

This shift in the way in translation work leads to the need for new directions for translator training, from the typical trial-and-error approach and error handling through comparative analysis, to an economic approach focusing on job requirements, matching assumptions and goals between requesters and providers and investigating the cost of errors for efficiency, use of resources, reliability, and affordability.