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> be more choosy about your training set and don't just snarf up reddit willy-nilly and go brrrrr That's a much more interesting (and complex) conversation. S

> be more choosy about your training set and don't just snarf up reddit willy-nilly and go brrrrr That's a much more interesting (and complex) conversation. Siphoning raw Reddit/Wikipedia is the closest you'll get to an honest snapshot of our internet-based society (for all of its tremendous flaws). One could make the case that we don't need an "honest snapshot of our internet-based society" to build a Translation app. But that's debatable... Being "more choosy" will inherently introduce a different set of biases. Perhaps those biases align more closely with our core beliefs and values - but they serve as bias nontheless.

hprotagonist 6y ago
No disagreement here! One thing that will absolutely raise some people's hackles is pointing out that "intentionally modulating biases in translation techniques" already has a name, and it is "being prescriptive about language usage". I've found that generally, tech/progressive/machine learning ethics folks tend to believe that prescriptivism is the domain of, for example, stuffy old people like Strunk and White, how dare they tell me what is "proper" -- and then turn right around and do just the same with a straight face but don't seem to really realize that that's what they're doing. At any rate, designers of such systems do need to face head on the fact that machine translation systems at scale both 1. need to reflect usage in the world in a descriptive enough way as to be useful and honest and provide coherent approximations of translation, even sometimes if it's reflecting perhaps unpleasant truths about ourselves we might not like to think about and 2. need to realize that their participation and choices of embeddings, etc., contribute to the corpus of texts in the world as well as reflect them, so their prescriptive choices are also real and will have feedback effects.

hprotagonist 6y ago

No disagreement here! One thing that will absolutely raise some people's hackles is pointing out that "intentionally modulating biases in translation techniques" already has a name, and it is "being prescriptive about language usage". I've found that generally, tech/progressive/machine learning ethics folks tend to believe that prescriptivism is the domain of, for example, stuffy old people like Strunk and White, how dare they tell me what is "proper" -- and then turn right around and do just the same with a straight face but don't seem to really realize that that's what they're doing. At any rate, designers of such systems do need to face head on the fact that machine translation systems at scale both 1. need to reflect usage in the world in a descriptive enough way as to be useful and honest and provide coherent approximations of translation, even sometimes if it's reflecting perhaps unpleasant truths about ourselves we might not like to think about and 2. need to realize that their participation and choices of embeddings, etc., contribute to the corpus of texts in the world as well as reflect them, so their prescriptive choices are also real and will have feedback effects.