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Artificial intelligence still has difficulties processing requests in one language, without the additional complications of translation. Michael Housman, chief data science officer at RapportBoost.AI, explained that the ideal scenario for machine learning and artificial intelligence is something with fixed rules and a clear-cut measure of success or failure. He named chess as an obvious example. This happened faster than anyone anticipated because of the game’s very clear rules and limited set of moves. Housman elaborated, “Language is almost the opposite of that. There aren’t as clearly-cut and defined rules.”

I asked Dr. Jorge Majfud, Associate Professor of Spanish, at Jacksonville University, to explain why consistently accurate language translation has thus far eluded AI. He replied, “The problem is that considering the ‘entire’ sentence is still not enough.” He noted that sarcasm and irony only make sense within this widened context. Similarly, idioms can be problematic for automated translations.

Dr. Majfud warned, “We should be aware of the fragility of their ‘interpretation.’ Because to translate is basically to interpret, not just an idea but a feeling. Human feelings and ideas that only humans can understand — and sometimes not even we, humans, understand other humans.” He noted that cultures, gender, and even age can pose barriers to this understanding and also contended that an over-reliance on technology is leading to our cultural and political decline. Dr. Majfud mentioned that Argentinean writer Julio Cortázar used to refer to dictionaries as “cemeteries”. He suggested that automatic translators could be called “zombies”.

David Pring-Mill. Why Hasn’t AI Mastered Language Translation? Internet: <singularityhub.com> (adapted).