Author: William Lise

A Not-so-Bold Prediction

Well within three years from now, most NES (native English-speaking) translators currently making their living translating Japanese-to-English will no longer be making their living by translating. And they will very likely not be doing post-editing of AI output either, as post-editing rates have already fallen to a level incapable of supporting even a modest lifestyle. What’s more, post-editing is also already being seriously discussed as a target for AI to at least partially handle, and that will lower the level of skills required of post-editors and, by extension, the rates earnable from post-editing.

By “most,” I envision no more than 10% of current NES translators remaining in translation three years from now to the extent that they can earn their living from translation.

Some of the people exiting translation might be able to find employment or work making use of their Japanese-language ability. Some have already done just that. Others will migrate to work unrelated to translation or language skills.

This is not a very bold prediction, as we can already see people leaving JA-EN translation, including highly skilled translators who expected to translate for much longer. It is ending, and people are leaving.

Suggestions that translators simply adopt AI themselves to allow them to continue working are delusionary and ignore the realities (1) that translation is a business and (2) that the businesses (translation brokers) that supply translation work to the vast majority of translators are already switching to AI for the translation process itself, this being a business decision that complaining translators will not be able to change. It is ending.

There are people and organizations to whom the above prediction or even discussion of its possibility is anathema. I would hope that they continue to observe where the profession is going as we move toward the end. It should come into focus for even the most optimistic observers.

Who gets to decide how good is good enough in translation?

Online interaction between freelance translators is filled lately with comments to the effect that translations created using AI are not good enough. Assertions are made that grave things will happen if AI is allowed to translate. Further assertions are made that clients will come back to “us” (to whom, I wonder?) when they realize the problems. And some translators posit that loss of lives and grave legal consequences will follow if AI is used to translate medical texts or documentation for machinery that could be dangerous if operated incorrectly.

All of these comments serve the very good purpose of what I call—borrowing from my NY upbringing—kvetch-bonding (wound-licking also comes to mind), between translators who feel they are being attacked on all sides by the migration of agencies to using AI to replace professional translators.

But most of the comments ignore the reality that the translation the kvetchers have been making their living from is, before—and, yes, even above—concerns over quality, a business, and people pursuing that business and their paying clients (translation consumers) get to decide whether a translation is good enough.

The subtext here is that most translators are not pursuing translation as a business, but have for decades—and to an increasing degree lately—been participating in what has been more recently been characterized as a gig-work economy.

The agencies have denied translators their agency in determining how they work. Requiring the use of specific software products and the use of hamster wheel translation platforms are good examples of this. Reverse auctions where translators bid jobs down are another. Of course, complicity on the part of freelance translators is a necessary element in making this gig-work economy function, and function it does.

Ultimately, as has been the case for as long as I can remember, the balance between cost and quality will be evaluated by and will inform business decisions by people in the translation business and their paying clients. The volume of translation work given to professional translators has significantly dropped precisely because significant numbers of clients are willing to bear the risks of lower quality if it is accompanied by a much lower cost.

No amount of complaining by freelance translators is going to change that. And the level of complaining among translators themseves, who cannot change things, reminds me of that old Chuck Berry song. Translators need to stop playing with their own ding-a-ling and interact with the people who can make a difference and who are making decisions about how good is good enough for them.

Translators will not be successful at moving agencies already heavily invested in efforts to eliminate professionals. That points clearly to clients who pay for and consume translations.

As a translator, your marching orders are clear. Can you hear the drums? Or are you playing with your…

Predictions: Premature, Wrong, and Spot-on

Over the years I have seen predictions come and go. Some go quietly when it is clear they are wrong, while others hang on, particularly if the predictor has a vested interest in having people believe the prediction, at least for a short time. Let’s take a look at a few.

More than a decade ago, MT reared its hopeful head, promising to make quick work of the annoyingly expensive process of translating one natural language to another. And it would do it at a fraction of the cost then incurred for what some thought was a necessary, but too-expensive evil.

At the time, most translators scoffed at the notion of an MT takeover, but more than a few translators were somewhat alarmed. A non-translator friend of mine asked me if I wouldn’t shortly be out of work, as computers were taking over.

Well, that prediction was a quite premature, but it appears that the introduction of AI is combining with not only a long-standing distaste for spending money for translations but also the realization that the good-enough paradigm is largely valid. The result has presented a very real existential crisis for many translators. The prediction was quite premature back then, but it has turned out to be correct.

Switching from the sublime to the ridiculous, we have the recent promise of flying cars, like something revived from Popular Science articles in the 1950s. This time, however, there are working models. But the catch is that flying cars are aircraft, with inevitable regulatory and safety requirements that will sink this dream before flying car startups go into production.

The chances are microscopically small of us seeing the skies over highways (or over anywhere, realistically) blackened by flying cars, piloted (or unpiloted), carrying passengers to their destinations without having to deal with traffic congestion down below. I think it is a safe bet that, for all intents and purposes, the flying car hype doesn’t amount much to more than showcasing of technology. A proof of concept does not mean proof of acceptance by a society and its regulators.

Turning back to languages, I ran across a book about writing systems today (Andrew Robinson, The Story of Writing, Thames & Hudson 1995) that I bought more than a decade ago at the British Museum. My motive was to learn about various writing systems that have evolved throughout the ages, and I was interested to see some of the things the author had to say about the Japanese writing system.

He effectively and correctly disabused readers of the commonly heard mistaken notion that kanji are ideograms that represent ideas and more properly characterized them as logograms, which represent words.

Then I encountered a section in which the author posits that kanji are on their way out.

It looks likely that the need for computerization must one day lead to the abandonment of kanji in electronic data processing, if not in other areas of Japanese life.

Written, as amazing as it seems, in 1995, this was clearly off the mark. I guess the author was a bit prescience-challenged. It is a shame that the author fell into this trap, particularly only a few pages after he correctly explained the large number of homophones in Japanese as the reason the Japanese are not able to easily abandon kanji. What, I wonder, would an AI system do with texts written only in kana phonetics? Something quite comical (or tragic), I would imagine.

Predications will continue, including those that are premature, wrong, and spot-on. Which they are only time will tell.