Tag: translation

It’s not that difficult: Translators, Interpreters, and Linguists

A surprising number of people seem to misunderstand the distinctions between translators, interpreters, and linguists. Worse yet is the misunderstanding that any of these categories of professionals should be expected to be able to do the job of the others.

Admittedly, even respected dictionaries leave room for—and can be accused of promoting—confusion between these terms. People spending large budgets on language services, however, should reasonably be expected to distinguish between these three terms of art in the field of language services. The differences are not difficult to grasp.

To be sure, there are a small number of people who cross the boundaries between the professions, but these are quite rare, and a translator should not be assumed capable of interpreting, or an interpreter of translating.

Translators

A translator engages in translation, which is the production of a text written in a target-language from a text written in a source language. Translators write words, but work without uttering a word that they are translating. A Japanese-to-English translator works from a Japanese source text, translating it into an English target text. Only a small portion of Japanese-to-English or English-to-Japanese translators are capable of interpreting between those languages, and most do not even want to be interpreters.

Interpreters

An interpreter engages in interpreting (rarely, but confusingly, sometimes called interpretation), which is the expression of a message spoken originally in the source language as a message spoken in the target language. While there are exceptions, most Japanese/English interpreters consider themselves exclusively interpreters and do not actively seek out translation assignments. Many of them would not be good translators.

Linguists

The term linguist is just a bit more problematical, because of a range of meanings. Strictly speaking, a linguist is a specialist in, not surprisingly, linguistics, which deals with the characteristics of language, including aspects such as structure, syntax, semantics, and origins.

In many years of serving the commercial translation market, we have encountered only a small number of working commercial translators who were also linguists, and have met very few linguists who are actively translating or who are even capable of translating or wish to translate as a profession. That separation is even greater when we consider linguists who might interpret. There are very few such people. Similar to the case of translators, interpreters and linguists are two quite distinct groups.

People who should know better, but don’t, misuse the term linguist, and some who know better, purposefully misuse the term.

You often see translation companies (particularly the ones more accurately characterized as translation brokers) boasting of all the “linguists” they have. This makes one wonder why they would talk about a group of professionals not generally engaged in or proficient at translation when they are trying to sell translation services.

Perhaps they think it makes the people they sell translations to feel better that their documents are being translated by people called linguists. Or perhaps they think that the translators they purchase translations from will feel better working for low rates if they can wear the title of linguist.

To be fair, there is the argument that linguist just means someone who is good at a number of languages, but professional translators realize that being “good at a number of languages” doesn’t mean you can translate.

There you have it, a short description of three often-confused professions. Although it might be optimistic for language professionals to expect people outside these fields never to confuse them, when a non-specialist such as a client gets it right, we feel more comfortable than when we need, for example, to inform an interpreting client that will we not be translating in their meeting or deposition.

Choosing what feels good is useful in avoiding facing what is true.

Adopting AI into your translation workflow is fine if it helps a translator and it provides a wonderfully anodyne topic for a conference presentation, while avoiding talking about the more serious challenges faced by freelance translators. But adopting AI will not get you work or be a survival solution if you are dependent on brokers for your translation work.

The translation brokers that most translators depend on for translation work are well into their shift to looking for only post-editors. They pay peanuts and you cannot live on peanuts unless…

Species of Translation Origin

Many countries, particularly ones with their own manufacturing capability or that are wary of products produced elsewhere, require products sold domestically to be marked with the country of origin.

Translation sellers have never had to fulfill that requirement and, in recent decades, the large translation brokers selling Japanese-to-English translation became power users of yet other translation brokers in China, where almost no translators have either Japanese or English as their native language. What could go wrong? Well, lots of things, but that is a topic for a different article.

Enter AI, and the problem of origin is escalated to one of whether a translation originated from a human or something else. Just as products of questionable origin have their origin laundered by having the product processed in some way in a respectable and trusted country, artificial translations can and do have their origins laundered by having members of our species process them to make them at least look usable. Translation purchasers and users should beware of such species of origin laundering.

There are good reasons why we do not use AI to translate.

Of Mice and Mousetraps

If you don’t have the budget or don’t want to pay for real cheese, you might try putting a photograph of a piece of cheese in your mousetrap, but don’t expect to catch anything but a photograph of a mouse, and an out-of-focus one at that. People who choose to use artificial intelligence to translate should not be surprised to find that they receive an artificial translation, and a poor one at that.

There are good reasons why we choose to continue to provide only professional translation.

AI takes Japanese-to-English translation back to the days when front-loading of quality was not that important, but this time with some new twists.

The buzz since last year in the translation business was all about AI and how it will revolutionize the way translations are done. Well, in some ways yes, but in one particularly important way, AI is taking people back to the past, when front-loading of quality in JA-EN translation seemed to be purposefully avoided, for reasons that varied depending upon the era we are discussing.

Throughout the evolution of Japanese-to-English translation, the globally shared inherited wisdom that a translator should be translating into their native language was largely ignored. The appearance of AI has made things worse in that respect. and it has actually presented the new twist of using a “translator” that has no native language and no understanding of the real world.

Japanese-to-English translation has a long history of not front-loading quality. The reasons varied, based on the operative belief system, the business requirements of Japanese selling and needing translations, and the availability and costs of translators at various times.

Stage One:  Native Japanese-speaking translators treated as mission critical

In the old days (for me, the late 1970s), significant numbers of people in Japan had never met a native English-speaking (NES) translator. Many believed that the reading and understanding of a Japanese source text needed to be done by a native Japanese-speaking (NJS) translator. How could a non-Japanese possibly understand the “uniquely” difficult language of Japan? There was a distinct resistance to using non-Japanese translators.

I would venture to guess (no guessing required, because it’s true) that the overwhelming portion of JA-EN translation was done by NSJ translators and then “brushed up” (as the expression was in those days) by someone else. That “someone else” was often a hapless native speaker of English enlisted to fix the translation, sometimes without the ability to read and understand the Japanese source text and without the advantage of familiarity with the subject matter. I personally know people who did such work. Having seen the output from NJS translators in those days, some of which made it into publications such as product catalogs, I know that the people involved in the production were not front-loading quality into the translation process.

Stage Two:  The rise of native English-speaking translators

As NES translators of Japanese became more common in the 1970s and 1980s, some people in the translation business and even a small number of translation consumers dared to entrust their documents to NES translators. Their translations required much less editing and usually no rewriting, but they were much more expensive than NJS translators. Even if the resistance to using NES translators could be overcome, however, there were not enough of them to handle the large volumes of JA-EN translation required. NJS translators thus were still dominant in translating Japanese into what was for them a foreign language. This was often (but not always) followed by editing at the hands of foreigners here in Japan. I know numerous people who were doing such editing work but who could not read the Japanese source text. It didn’t matter; they were still just “brushing up” the translation to make it presentable.

Stage Three:  Chinese translation brokers enter the Japanese-to-English translation business

Around the end of the first decade of the 21st century, numerous large translation brokers in the US began using translators and other translation brokers in China to do JA-EN translation, done by translators who have native ability in neither the source language (Japanese) nor the target language (English). They were what I will call third-language translators (TLTs). What possibly could go wrong?

Well, an examination of documents translated JA-EN by people in China reveals that, although such translations are dirt cheap, they are very often of poor quality, often including serious mistranslations. This is not surprising, since many of the translators could probably never have experienced Japan or the Japanese language first hand, but only from China.

Again, this approach does not place value on front-loading of quality in the translation process, but rather takes the approach of quick-and-dirty translations that are then (perhaps) subjected to repair work to make a document usable.

Stage Four:  Enter AI

In the second decade of the 21st century, AI that could produce translations of a sort—the sort being artificial translations—appeared. It promised to totally up-end the translation process, but actually tends to offer a number of problems even the previous faulty approaches didn’t have.

Professional translators, we are told, are too expensive and not needed, and the solution is AI. We are told that AI machine translation can be sufficiently improved in quality by a new breed of workers called post-editors.

Well, this might work for some types of translation, providing expectations can be sufficiently lowered, but the presence of artificial intelligence that produces artificial translations means that the process returns to one in which front-loading of quality is ignored, with a number of additional problems. Specifically:

  • Whereas professional translators have real-world experience and understand the subject matter, AI lacks both essential qualities. It never “gets out” into the real world and it understands nothing, beyond its attempt to emulate the writing behavior of a professional translator by statistical learning from cyberspace content, and it often fails to achieve a sufficient level of quality.
  • Whereas a professional translator knows their strengths and weaknesses and can decline a job if the translator’s capabilities would be exceeded, AI doesn’t care about quality and doesn’t need to decline a job because of lack of knowledge or translation ability. It just goes right ahead and produces a translation, the assumption being that it can be fixed later. Essentially, this is a programmed Dunning-Kruger effect.

Throughout the four stages of JA-EN translation, there have been varying levels of front-end loading of quality into the translation process. The best shot the JA-EN translation business had at front-loading quality was back in the days when native English-speaking translators became more common. Those days are coming to an end for a large portion of the translation that is sold, because it is shifting rapidly to AI.

Promoters of AI take us back to not front-loading quality, using a process that has native ability and understanding of neither the source nor the target language. Another significant problem is that deceptively good English—produced at breathtaking speed and ostensibly extremely low costs—can blind people to the problems involved behind the curtain of the human-like English.

The players have changed, but this time there are problems that are not faced when professional translators were used. Perhaps it is time to modulate the AI translation hype just a bit.