Integrating Machine Translation into Translator Training: Towards ‘Human Translator Competence’?

Abstract

This article proposes a re-thinking of translator competence in the face of the rapid and dramatic technologization of translation. Drawing on the concept of translator competence and the social constructive approach to translator training, the article aims to focus on a pathway to be followed in order to delineate a competence that exclusively pertains to the human translator who is supposed to compete/collaborate with the machine now and in the future. Such delineation would involve adding ‘human’ to ‘translator competence.’ With this aim, the article presents the results of a learning practice designed to integrate machine translation (MT) into translator training to help translation students raise their awareness of their ‘professional self-concept’ as human translators. On the basis of the results, the article suggests that it would be of help to integrate MT into translator training as early as possible with a focus on helping translation students raise their awareness of their existing and potential roles as human translators, whose roles will not be limited to post-editing and pre-editing and will include training MT systems, selecting and assessing training data and collaborating with MT developers as expert human translators. Moreover, the study argues that such awareness would also lead to a further awareness that students need to ‘learn to learn’ (i.e., to become lifelong learners) in order to continue to confront the unknown and unpredictable future challenges MT would pose and embrace the opportunities it would offer.

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