Machine Translation - Evan

    Picture a young boy, aged 11 or 12, sitting restlessly in his middle school French class. He had been up late the previous night and had not had the time to properly complete a crucial assignment, so he absentmindedly pulls out his phone, tapped a few keys, and zoom, zip, zop- Google Translate pulls up all the answers he needed. Or, rather, what he thought were the answers he needed. Yet, when looking over his assignment with his teacher later that day, he realizes glaring mistakes. The errors are blatant, like a coffee stain on a white buttondown. 

This was my first realization of how lackluster machine translation is. As it turns out, no translation A.I. can wholly and properly maintain the nuance, connotation, and tone from language to language as well as human translators can. For example, Johnson says, "A novel legal argument, says the translator in Madrid, needs to be almost entirely translated by hand. This is not doable by someone who merely knows Spanish and English and took a few translation classes. The bad news for some translators is that a spigot of repeatable, easy work is being turned off. The good news is that what remains will be brain-challenging stuff for people who have a knowledge of a language and something else,". 

Similarly, another Economist article reads, "Fully automated, high-quality machine translation is still a long way off. For now, several problems remain. All current machine translations proceed sentence by sentence. If the translation of such a sentence depends on the meaning of earlier ones, automated systems will make mistakes. Long sentences, despite tricks like the attention model, can be hard to translate. And neural-net-based systems in particular struggle with rare words."

This is most accessibly clear if one were to copy and paste a large chunk of text into Google Translate. Suddenly, adjectives are misplaced, predicates are missing, adverbs turn to adjectives-- it's a mess. 

However, I think that in recent years, what has been the most egregious example of how machine translation simply cannot compare to human translation, is that of social media websites' translators. For instance, take the Instagram caption below.

The meaning of 現像してきた is not only lost but it is completely mistranslated.

I primarily discussed Google Translate and social media websites' translation tools, however, a much more powerful tool such as DeepL is certainly both promising and scary for the prospects of translation. The fact that it is used so ubiquitously shows its efficacy, however I still believe that human translators will be necessary and used in the near future (and hopefully beyond....!).