Are Translators Losing Their Jobs Because of Machine Translation?

Quite many professional translators are afraid that they will be replaced by emerging technology: machine translation. Machine translation would take their jobs or at least lower their salaries. I made some Internet searches and found interesting numbers. This article is about how many translators are needed to satisfy the communication needs in the whole world.

Please note that the following calculations and numbers are estimates and intended to give just a rough understanding of the situation.

For one professional translator translating 2000-2500 words per day seems to be quite a normal result (sources: Proz, Tips for Translators). Naturally the speed depends on the language and the translator. But we can use this number to calculate our rough estimates.

On one page there is on average 300-500 words. (source: When we combine this information with the average translation speed we conclude than an average translator can translate roughly 4-9 pages per day. Let’s use the average of 7 pages per day in our estimation.

Estimates of the total number of professional translators in the whole world vary between 150 000 and 300 000 (source: T&I Business).In the world there are currently over 6 900 000 000 people (source: Wikipedia). That is, below 0,005% of us work as professional translators. It is 20 000 people per one translator. To employ one translator 20 000 people (or companies they work for) should buy translation of 7 pages per day.

What do you think, is there enough work for all the translators, considering both the emergence of machine translation technology and that world trade and communication between people via Internet is growing fast?

My personal feeling is that 20 000 people (and the companies they work for) could use a lot more translations that just 7 pages per day. To me it seems there should be plenty of work even for more translators than currently exist. Maybe the prices of translations are preventing translation volumes from growing substantially?

Proofread Machine Translations To Avoid Muprhy’s Law

I want to share with you a real life example of the cruel Muprhy’s law. Like I wrote in a previous post, proofreading and it’s importance should be taken seriously. While Murphy’s law says that everything that can go wrong will go wrong, Muprhy’s law states that everything that can be written wrong will be written wrong – especially if you write about proofreading.

One of the latest victim of this ruthless law is Adam Wooten. His article about importance of good brand translations in foreign markets in a business magazine had missed the final proofreading with some unwanted consequences. In this case the author can’t be blamed for the mistake because the last modifications were made by the magazine staff. No matter who’s to fault, Adam Wooten was very disappointed about the issue. I won’t go to the details but you can read his somewhat bitter statement in its entirety here.

This case illustrates once again how important it is to proofread translations. We have discussed about machine translators many times in this blog. Although we are encouraging people to try automatic translations to save time and money, we are also talking about the fact that machine can’t meet the translation quality of professional human translator. Furthermore it is important to highlight that machine translation is a fast access to a huge amount of information written in foreign languages. Machine translation is an effective tool for the right places.

Are we just too lazy to do the final proofreading?

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Guidelines For Writing Text That Machine Can Translate Better

Machine translation is potentially a very effective technology. However, it is not 100% reliable and can not translate everything. The reliability of translation depends on the languages that are translated and especially on the text to-be-translated. By following certain, simple guidelines you can write text that machines can translate better.

1. Write short sentences.

When one sentence carries one meaning it’s easier for a computer to translate. Long, complicated sentences containing sub-clauses tend to be more difficult to translate. We recommend maximum of 25 words per sentence.

2.Write full, grammatically correct sentences.

Humans can understand more than computers. If you leave some words out of your sentences humans can usually nevertheless understand your meaning. However, computers will make more mistakes. The more possibilities there are for misunderstanding, the more mistakes machine translation will make.

3. Use common vocabulary.

Keep your language simple and use words that you use in normal language. Also note that machine translation can not usually translate specialized words well. For example, legal, medical, engineering etc. texts often contain special, field-specific words that the computer can not translate.

4. Avoid words that have several meanings.

If you use words that can be understood in several ways it’s likely that sometimes your meaning will be misunderstood. Therefore, when possible use words that are impossible to misunderstand.

All this can be summed up in one mnemonic: write text that is easy to understand and difficult to misunderstand. When you follow these guidelines your text will be easier to translate with a computer. And most of all, your text will be easier to understand by your readers too!


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Machine Translation: Friend or Foe For Human Translators?

Machine translation has a negative echo in many human translators’ ears. Many professional translators are afraid that as machine translation gets better and better, less and less human work is required and human translators might eventually lose their jobs.

Please consider this example. In the early 1900 car had just been invented. It was a new, exclusive technology. Car’s were difficult to manufacture and they were very expensive. What happened when Henry Ford developed ways to manufacture cars more efficiently and cheaply? One could think that some auto-workers lost their jobs because less people were required to manufacture a car. Instead, the opposite happened. The number of auto-workers increased dramatically because, thanks to more efficient and cheaper production, more and more people could now afford a car. Earlier middle or low income people had no chance of buying a car. When the car prices had sunk suddenly a lot of people could afford to buy a car and, in fact, actually bought one.

Now compare the professional translator’s situation to auto-worker’s situation. What will happen to professional translators when machine translation is making their work more effective? Will the professional translators lose their jobs? Or will the same happen with translators as with auto-workers in early 1900, when more and more companies and even private persons can really afford to buy translation and buying translation is becoming so easy in internet?

Machine Translation – What It Is?

Translated Machine Translator

Machine translation refers to a piece of text which have been written again from one language into another language by a machine. Nowadays the term ‘machine’ is usually the same as computer in this context. Because, unlike Thomas Watson, the chairman of IBM at that time, famously stated in 1943, computers have become the most important tools in many aspects of human life and because machine translation is relatively new term, it is useful to explain the concept a little more.

Practically speaking, machine translations are made with the help of an existing translation memory. This kind of memory can be a lot of things, but basically it is a file containing the same text written in more than one languages. For example any electronic dictionary can be used as a translation memory. Machine translator then uses the memory as a source for translations. This evidently leads to the situation where the more comprehensive the translation memory the better the translation quality.

Computers can perform machine translation with or without an Internet connection. Perhaps the most known online machine translation provider is Google with its free Google Translate -service. Online machine translation can utilize online translation memory while offline machine translators must have their own memory. Both of these methods have their pros and counts: online memory can be very huge and automatically updated, but at the same time they are public and no one can really control them. Offline memories on the other hand can be strictly controlled by the user but they have to be manually collected and updated.

This was a very short overview of machine translation. If you want to take a deeper look at the world of machine translation, you can read the article in Wikipedia for example.

How would you define the term ‘machine translation’?

Using Machine Translation Is Like Driving a Car

I like to compare machine translation to driving a car. We all know how convenient and useful it is to travel to various places with a car. And many of us can and have a license to drive a car. Driving a car is a skill that has to be learned. When one has learned to drive a car, it is easy and useful to use the skill. But driving has some crucial limitations. Even when one can drive a car well, it is not possible to drive with the car anywhere, for example in the forest or from Europe to Australia or to the Moon. One has to stay on the road and on the solid soil. The situation is very similar with machine translation. One must know when and how machine translation can be used.

Machine translation is not a turnkey solution to all possible translation problems. One must know when machine translation can be used and especially how it should be used. For example, if you expect a computer to translate literature perfectly from one language to another you will surely be disappointed. But if you want to communicate simple matters to another language you might be positively surprised.

I would like to emphasize that machine translation is potentially a very effective tool that must be used correctly. Like a car, you must first learn how to drive it and where you can drive with it. Same applies to machine translation. Luckily, using machine translation is far, far easier to learn than driving a car.