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It‘s terrible and sad. Even more so because AI still gets things wrong all the time.
I know someone who was a translator between two (less widely spoken) languages, and some specifics I recall from our conversations about work:
- Sometimes the translations use many technical terms, and getting those wrong (trusting LLMs) is not an option. (This was for some patents IIRC)
- Some terms simply do not exist in another language, and it could be up to the translator to invent a term to define and carry the information across. (This was for some government digital service, and the term was similar to “digital queue”)
- Tone and nuances are very difficult to translate. Phrasing can have implications and connotations. (Simplest example: “i am afraid” does not imply fear, it’s an established politeness phrase) Neutral in one language could be viewed as hostile in another, too. (And with politicians being petty, could have consequences)
None of those would be addressed with LLMs. Small training set for language (and language being similar to a few others) is an issue. Anything technical or non-existing would be prone to hallucinations. And tone is difficult enough to convey through text to begin with, let alone with LLM translation.
Unfortunately it doesn’t have to be better than the worker, we all know this sucks at most of the things it’s being touted as great at.
It just has to convince management who make decisions that it’ll save money (or that they can spin it that way) for the next quarter. That alone is enough to destroy people’s lives.
My company thankfully still employs simultaneous interpreters for meetings and has one translator on staff. I think, at least in part, because of how bad translation tools can be from EN <> JA.