The concept of AI collaboration remains somewhat controversial in the translator community. Much has already been said about the impact of AI on more language-centered tasks such as translation, but what about AI in a broader sense? An increasing number of linguists now collaborate in AI training tasks such as image annotation or speech recognition, categorizing or annotating the data which ‘teaches’ AI systems. But is this an interesting new sideline for linguists, or something of a step down in the world?
On the one hand, AI training work does not necessarily require the same degree of qualification or experience that translation does. Yet in many ways the skill set is quite similar. AI data training relies on many of the qualities that are innate to linguists, such as strong analytical skills, attention to detail, and critical thinking. The fact that not every collaborator will complete a given task to the same level of quality also suggests that there is a relatively high degree of finesse involved even in fairly routine AI tasks. In this sense, we could argue that AI collaboration provides a wealth of interesting opportunities for skilled and experienced translators, even if only as a sideline to language work.
On the other hand, there are those who argue that the often fairly repetitive nature of AI training work can make it frustrating for translators, who might easily miss the more creative or ‘human’ elements of language-focused work. The fact that AI work is generally open to a much larger pool of people than translation work can also mean that translators, who may have extensive experience or education, feel that it is less valued than more ‘traditional’ language work, and therefore less worthy of their consideration. This could lead to linguists feeling that AI training work is not an appropriate outlet for their talents.
Having presented some of the arguments for and against machine learning work, it’s now over to our translator community. Does AI training work inspire you or fill you with dread? Do you feel it’s worthy of your time as a linguist? Feel free to add your voice to the discussion below!