Re:The Shallowness of Google Translate
by YeGoblynQueenne on Monday February 05, 2018 @08:35PM
(#16313822)
>> No-one is saying Google Translate is on par or anywhere near human translation.
Well, they kind of do. Like I say elsewhere, the common measure of machine
translation performance is a family of metrics like BLEU or ROUGE that basically
compare machine translation to human translation. So when a research team
claims strong performance in machine translation, they're really saying that
their systems can do the kind of translation that humans can do, in a very
literal sense (of similarity between tokens or n-grams). Besides, like
Hofstadter says, Google has often claimed its NLP systems (for example, its NL
Parser, Parser Mc Parseface) approach or outdo human performance.
Google is quite unrealistic in the way it promotes its technology and claiming
it does better than humans is its bread and butter in this regard.
>> Frankly, it sounds to me as if you feel threatened by this development.
I don't have any reason to feel threatened :) I'm a machine learning PhD
researcher with some hands-on experience of NLP (though not machine
translation specifically- I've only theoretical knowledge of it). I have a
background in foreign languages and translation, but not professionally.
If I can summarise my concerns, it's not that I'm worried that machine
translation will become so good it will take the jobs of human translators.
I'm worried that we will keep replacing human workers with bad AI and end up
making our lives a lot worse in the process.
Well, they kind of do. Like I say elsewhere, the common measure of machine translation performance is a family of metrics like BLEU or ROUGE that basically compare machine translation to human translation. So when a research team claims strong performance in machine translation, they're really saying that their systems can do the kind of translation that humans can do, in a very literal sense (of similarity between tokens or n-grams). Besides, like Hofstadter says, Google has often claimed its NLP systems (for example, its NL Parser, Parser Mc Parseface) approach or outdo human performance.
Google is quite unrealistic in the way it promotes its technology and claiming it does better than humans is its bread and butter in this regard.
>> Frankly, it sounds to me as if you feel threatened by this development.
I don't have any reason to feel threatened :) I'm a machine learning PhD researcher with some hands-on experience of NLP (though not machine translation specifically- I've only theoretical knowledge of it). I have a background in foreign languages and translation, but not professionally.
If I can summarise my concerns, it's not that I'm worried that machine translation will become so good it will take the jobs of human translators. I'm worried that we will keep replacing human workers with bad AI and end up making our lives a lot worse in the process.