Machine Translation Shifts Power
thegradient.pub
thegradient.pub
You’re not wrong in the one dimension that people preserving a culture are by definition “losers” (otherwise it would take no effort to preserve), why don’t we try not punishing kids for speaking their mother tongue and see how that goes for a while?
I guess if that's what people believe, it may be tough to convince them otherwise... but IMO, it's really valuable to think about how the "winners" of history navigated tough moral challenges, and often did things that we can now identify as harmful.
In this case, it's not about making historical missionaries feel bad about themselves for "winning" -- this article (in my read, etc) is concretely about trying to avoid repeating these mistakes in modern tech, specifically NLP and translation. We can (hopefully) do better as a society than "might makes right"!
Or maybe its a sign that winners couldn't completely eradicate it because it occupies a niche in a more optimal way than the winner. Infact, we have seen winning cultures fail while the niched "loser" culture maintains, only to thrive after the downfall of the temporary winner.
Some of the first grammar resources for previously unwritten languages were created by Christian missionaries in order to translate the Bible and proselytize to indigenous peoples worldwide. History is rife with examples of colonial subjects who were forced to learn the languages of their colonizers, often facing punishment for speaking in their native languages.
Surely any reasonable person would see that translating books into a language promotes, not suppresses, that language. Yet she links one to the other without missing a beat.
That's because the article's conclusion was written first, then filling had to be added to reach the pre-agreed conclusion.
As for the article, it reads like teenage-angst Marxism.
Any task "offloaded to the machine" will always carry some level of power-shifting that is frequently under-noticed, and I'm surprised I haven't seen this concept expressed in a more general way?
The NSA doesn't have superpowers. They have a lot of competent people, paid to work on topics that are are important to state security, but I think they are lagging behind on topics with profitable commercial applications. And machine translation is one of these.
The reason I think that is that working for a three letter agency comes with a burden of secrecy, and obviously, people tend not to work as efficiently if they are not allowed to talk to each others. These institutions are also plagued with pork-barrel economics, and secrecy is also a good way to hide incompetence.
So if a private company can do it, it is better to let them do.