With increasing acknowledgment of enhanced quality now achievable by
Machine Translation, new possibilities have emerged through collaboration
between human and machine in the translation process, including providing
varying qualities of translation in response to quality/efficiency requirements.
This paper presents surveys of post-graduate students of translation
conducted over four consecutive years to examine if their awareness and
preparedness have kept pace with these possibilities. It is found that respondents
across the years generally perceive their awareness as lacking, are hesitant
in employingMT, and show marked reservations when reconsidering
issues such as quality and the preeminent position of the human translator.
A review of existing research in translator training points towards a lopsided
emphasis on linguistic competence and standalone courses for introducing
technology as the primary cause behind low adoption. The need of the hour
is translator training that fully integrates technology in the translation
process and also provides a clear framework to adjust quality/efficiency is
important to ensure preparedness. A repeat survey of students from 2021
who were trained under this model shows an increase in willingness to use
MT and to consider quality as dependent on intended use. The focus here is
on Chinese-English translation, but the discussion may find resonance with
other language pairs.