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.