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Why Machines Alone Cannot Solve the World`s Translation Problem

Sixty years ago this week, scientists at Georgetown and IBM lauded their machine translation solution known as the 701 computer. The computer had successfully translated multiple sentences from Russian into English, leading the researchers to confidently claim that translation would be fully handled by machines in "the next few years."

Google’s new method -- one that is meant to complement, but not replace their statistical approach -- uses data mining in order to compare the structure of one language to another, and then generates phrase tables and dictionaries accordingly.

What does this mean? Even Google isn't satisfied that statistical machine translation will move things along quickly enough. That method has its limitations, just like all methods do. However, machine translation is not going to replace professional human translators anytime soon. Here are six reasons why:

1. It's Tough to Get Good Translation, Even From Perfectly Bilingual Human Beings.

One of the reasons that machine translation cannot replace professional human translation is the same reason that plain old bilingual laypeople, for many tasks, cannot replace professional human translation. For most translation jobs, the task of translation requires more than just knowledge of two languages. The idea that you can simply create one-to-one equivalencies across languages is false. Translators are not walking dictionaries. They craft beautiful phrases and sentences to make them have the same impact as the source. Machines cannot exactly do that.

2. Translation Quality is Highly Subjective.

Even if machines could approximate human translation quality, it's unclear which version of human quality they would emulate. Give a text to 100 human translators, and you'll get 100 different translations. Which one offers the best "quality?" In many ways, this is like asking someone which rendition of a song is best when sung by 100 different singers.

3. There Are Too Many Languages Out There.

Google Translate today supports 80 languages. There are between 6,000 and 7,000 languages alive today, of which about 2,000 are considered endangered. If we use a very conservative estimate and say there are only 1,000 languages of significant economic importance in the world today, that still leaves 920 languages yet to be developed.

4. Most Languages Are Not Written.

The vast majority of the world's languages are spoken or signed. Online, much of our communication is migrating from text to a combination of text plus audio, and even more importantly, video. This means that written language need not be the barrier it once was for people whose languages lack written forms. It also means that translation has its limits. This doesn't mean that text translation won't be important. It might just mean it will increasingly take place behind the scenes, with audio or video output instead.

5. Context Is Key.

In a language like English, a single word can have hundreds of different meanings, depending on the context. Word-for-word translation is impossible, so instead of thinking about words, when humans use context to figure out meaning, we think not just of single words, but how those words interact with the ones around them. Those combinations are constantly changing and multiplying, limited only by human creativity. Machines can hardly keep up.

6. Language Is Simply Too Important.

How important are the words your company uses to describe its products or services? They are critical. For many companies the voice of the brand all centers around word choice. How human beings make choices about the products they buy and the services they use relates directly to the words that are used to market and sell them. Our taste or distaste for a particular term often relates to our upbringing, our culture and even our past experiences. Humans cannot accurately predict which words will annoy or confuse even the people we know best. How can we expect a machine to fare any better?

The bottom line is this: Computers will never fully solve the translation problem, and even to make micro-strides toward that audacious goal, they will need significant help from humans. The question isn't, "Will we get there?" but rather, "How far will we get, and how fast?"

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Our latest news

Translation tech gets Olympic push

Japan may not be the best in the world when it comes to speaking English, but it remains a pioneer in developing cutting-edge translation technology.
With the 2020 Tokyo Olympics approaching, the nation is once again plotting to surprise the world, this time with high-quality, real-time machine translation systems.
Public and private institutions are working eagerly to develop and upgrade the technology so it can easily be used by tourists, whose numbers are growing sharply

Preparing for Machine Translation: What Machines Can and Can't Do

There is nothing especially novel about machine translation, a technology that reaches back to 1951, when a team from IBM and Georgetown University first demonstrated a computer’s ability to translate short phrases from English into Russian. In 63 years, the machines involved in machine translation have evolved. What a warehouse-sized computer could do in 1951, a laptop can do even better today.