There are still some 'editor' positions, however they don't pay very well and I'd imagine they won't be around long either.
There are still some 'editor' positions, however they don't pay very well and I'd imagine they won't be around long either.
Try in ChatGPT asking it to translate some passage of relative complexity into idiomatic Thai. Start a new chat. Ask it to translate the Thai, pasted in, into idiomatic English. This was always a way to test how bad exactly Google translate is. It’s essentially flawless with ChatGPT.
I showed my brother in law, who is Thai in Thailand and who works for an English speaking multinational. It’s revolutionized his job. He struggled to be understood, and struggled with Google translate to make something understandable. Now he’s able to conduct his business without friction.
More regular "business" translation will probably be displaced by AI tools.
In general the default should flip from it can't do x to it can do it until ypu tried it and verfied it.
Also, be sure to retest with every new release.
I had some modest experience with this and “thrived” doesn’t line up with how the translators I worked with described it even a decade ago – they loved our project because we valued quality, whereas most of the work they were seeing was rapidly declining wages because Google Translate was good enough to get businesses to decide they didn’t need to pay much for humans.
I’m pretty sure you’re right that this is the death knell for translation as a career unless it’s in combination with some other scholarly skill.
Fully automatic transcription by AI is a very, very hard problem, based on my experience of many of the jobs I got*. The automatic transcription makes the work 10X easier now though by applying a first pass that gets you 90% of the way and then humans like me come in and fix it all up.
* One hard example was a motorcross race commentary where it was necessary to know which riders the commentators were referring to based on their amusing and sarcastic comments, the nicknames of the riders, and deal with the fact the audio was 99% revving engines.
People have been predicting speech recognition replacing human secretaries since the 1950s, starting with https://en.wikipedia.org/wiki/Dartmouth_workshop
You don’t have to get rid of all jobs in a field for it to have major impacts.