‘Your United States was normal’: Has translation tech really made language learning redundant?

Credit: Unsplash/CC0 Public Domain Every day, millions of people start the day by posting a greeting on social media. None of them expect to be arrested for their friendly morning ritual.

But that’s exactly what happened to a Palestinian construction worker in 2017, when the caption “يصبحهم” (“good morning”) on his Facebook selfie was auto-translated as “attack them.”

A human Arabic speaker would have immediately recognized “يصبحهم” as an informal way to say “good morning” . Not so AI. Machines are notoriously bad at dealing with variation, a key characteristic of all human languages.

With recent advances in automated translation, the belief is taking hold that humans, particularly English speakers, no longer need to learn other languages. Why bother with the effort when Google Translate and a host of other apps can do it for us?

In fact, some Anglophone universities are making precisely this argument to dismantle their language programs .

Unfortunately, language technologies are nowhere near being able to replace human language skills and will not be able to do so in the foreseeable future because machine language learning and human language learning differ in fundamental ways. How machines learn languages

For machine translation , algorithms are trained on large amounts of texts to find the probabilities of different patterns of words. These texts can be both monolingual and bilingual.

Bilingual training data comes in the form of human-translated parallel texts. These are almost always based on the standard version of the training language, excluding dialects and slang phrases, as in the example above.Diversity is a characteristic of all human languages, but diversity is a problem for machines. For instance, “deadly” means “causing death” in most varieties of English, and that is what appears in the training data.The Australian meaning of “excellent” (from Aboriginal English) puts a spanner in the works. If you […]

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