Three Reasons Why Machine Translations Fail
The idea of machine translations can be an appealing one — particularly in the fast-paced world of social media. After all, who wouldn’t want a Facebook post, Tweet, or other social media communication perfectly translated within mere milliseconds? Except the thing is: machine translations are rarely perfect. In fact, despite strides in recent years, machine translations are often deeply flawed. Let’s take a closer look at three reasons why machines are an inferior solution when it comes to social media translation.
Translation is Not Linear Translators do not simply look at a word and replace it with another. Why not? Because words in one language do not always directly translate with words in another language. Instead, translators use their comprehensive knowledge of two or more languages to create phrases and sentences with the meaning and impact of the original text. For the same reason that bilingualism doesn’t automatically qualify an individual to be a translator, machines are inferior for this task for which skill supersedes statistics.
Translation is Subjective The subjectivity of language makes translation incredibly complex, and far more than a matter of matching word-to-word equivalencies. However, machines are not capable of subjectivity. While humans look at a translation project and see infinite possibilities, machines see just one. The result? Limited — and often inaccurate — machine translations.
Factor in cultural differences and language nuances which are incredibly difficult for intuitive humans to pick up on let alone non-sentient machines, and relying on computer translations can be a recipe for disaster.
Context Matters When you were learning to read and came across a particularly challenging word, you were likely encouraged to look at the context in order to derive meaning. The same concept applies to translation: context is critical. Words don’t exist in a vacuum; they interact with the words around them. While human translators evaluate a complete text to derive holistically accurate meaning, machines can only look at words. In many cases this misses the point.
One last thing to keep in mind when considering machine translation services? No matter how much technology advances, businesses are still made and broken on human relationships. While social media facilitates how we communicate with each other, what we communicate remains in our domain. Are you really willing to leave your critical communications up to machines?