{"id":5744,"date":"2017-06-28T07:55:36","date_gmt":"2017-06-28T11:55:36","guid":{"rendered":"https:\/\/blogs.transparent.com\/language-news\/?p=5744"},"modified":"2020-10-01T12:28:05","modified_gmt":"2020-10-01T16:28:05","slug":"learning-a-foreign-language-is-not-obsolete","status":"publish","type":"post","link":"https:\/\/blogs.transparent.com\/language-news\/2017\/06\/28\/learning-a-foreign-language-is-not-obsolete\/","title":{"rendered":"Learning a Foreign Language Is Not Obsolete"},"content":{"rendered":"

In 2011, Michael Sinanian claimed<\/a> that \u201ctranslation technology will evolve within the next five to ten years to make the process instantaneous and transparent to the end-user, rendering foreign language competency effectively\u00a0useless.\u201d It\u2019s not the only claim of its kind, though it is one of the most audacious.<\/p>\n

Well, it\u2019s been 6 years and we\u2019re still nowhere close to finding foreign language skills \u201cuseless.\u201d<\/h5>\n

Yes, machine translation has improved markedly<\/a> in recent years,<\/strong> learning to treat languages as more than just \u201cwords in a bag.\u201d But it\u2019s still far from perfect\u2014it\u2019s not even passable. Run any paragraph through Google Translate and you\u2019ll see why. For professional purposes, when a business deal or matters of national security are at hand\u2014rough is not good enough.<\/p>\n

Yes, speech recognition is becoming more sophisticated<\/strong>\u2014we use it ourselves in Transparent Language Online. But anyone who has had a conversation with Siri or Alexa knows it\u2019s not nuanced enough to replace<\/em> real human communication. Not to mention major players like Siri, Cortana, and Alexa understand less than 2 dozen languages total. These and other speech recognition technologies have a lot of language left to learn, in terms of both breadth and depth.<\/p>\n

Yes, artificial intelligence is doing better with context and meaning.<\/strong> Computers are getting better at dealing with natural language<\/a>, recognizing analogies, homophones, \u00a0and so on. The onset of AI-powered translation earpieces<\/a> also looks very promising. But those devices are limited by the same problem that plagues all devices: tech failure. Headphones break. Batteries die. Machines freeze. Human language competency will always have their place, if not as the central form of communication, as least as a backup or control.<\/p>\n

These advances in automation and machine learning also mean companies need more people<\/em> capable of analyzing and understanding all the big data involved. Business mogul Mark Cuban believes<\/a> that demand for liberal arts major\u2014language majors in particular\u2014will increase<\/em> as a result:<\/p>\n

\n
\u201cI personally think there’s going to be a greater demand in 10 years for liberal arts majors than for programming majors and maybe even engineering,” Cuban said. He cited degrees such as English, philosophy, and foreign languages as being the most valuable.\u201d<\/h5>\n<\/blockquote>\n

AI companies, for example, are already<\/a> turning towards linguists to help with product development and customer service. While developers create the actual code, people from language backgrounds are brought on to ensure natural language processing.<\/p>\n

Even if advances in speech recognition, machine translation, and artificial intelligence do reach the point that Sinanian predicts, there are other valuable reasons to learn a language.<\/strong> Speaking someone\u2019s language is a verbal sign of respect\u2014it can bridge cultural gaps and create instantaneous bonds among diverse people. Language learning also bestows cognitive benefits,<\/a>\u00a0encourages critical thinking, and boosts cultural competency. Even if or when a machine can\u00a0<\/i>do the talking, it is critical to know how a culture views time, politeness, and other values. Even non-verbal miscommunication can spoil a deal, risk a negotiation, or derail a potential friendship.<\/p>\n

We couldn\u2019t agree more with Sinanian that technology will \u201celiminate cultural barriers and thus enhance global human cooperation\u201d\u2014it\u2019s part of our mission. But we can\u2019t foresee any technology, no matter how revolutionary, that obviates the need for human language learning. After all, what\u2019s human cooperation or connection without real human communication?<\/strong><\/p>\n

Instead of focusing on how tech could replace language learning, we look at how tech can enhance language learning<\/a>. To that end, we\u2019re not 5 or 10 years out from seeing revolutionary results. We\u2019re seeing it every day in our language training programs. Learn more about how we’re transforming the economics and logistics of language learning here<\/a>.<\/strong><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"\"\"

In 2011, Michael Sinanian claimed that \u201ctranslation technology will evolve within the next five to ten years to make the process instantaneous and transparent to the end-user, rendering foreign language competency effectively\u00a0useless.\u201d It\u2019s not the only claim of its kind, though it is one of the most audacious. Well, it\u2019s been 6 years and we\u2019re…<\/p>\n

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