.@OpenAI controversy, no one (including me) talked about #ethics of using @reddit for training. It is toxic to #women #minorities. I was harassed and threatened on @mxlearn when I spoke up about #NeurIPS @Miles_Brundage @jackclarkSF can u comment on this choice? @samcharringtonhttps://twitter.com/__yoson__/status/1101593216992849920 …
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I think the q of appropriate data sources for large-scale, generally released models is a really great topic for discussion. It seems like there's some value to the inherent heterogeneity of sources that get linked to from various social forums. What might be a good source?
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I agree, there isn't a great answer to that, given how biased internet is. Techniques like debiasing word embeddings can help remove bias to some extent. When
@OpenAI model was covered by journalists, bias was never highlighted. https://arxiv.org/abs/1607.06520 - Show replies
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we also applied a blacklist to a bunch of subreddits that have known abusive/malicious content - sharing more here in a bit hopefully
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Reddit collates huge amounts of natural text in a relatively open form. Wikipedia has stilted formal language. Reddit is horrifically biased (and they seem to have tried to mitigate this) but where else are you going to get that much natural text?
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As
@jackclarkSF mentioned, we hope to share more of our approach to the bias issue very soon. Agree it’s a key concern! -
I think that humanity is biased and we should avoid all their data where possible ;-)
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reddit is not that bad, the value is real there even if there are outliers to prevent biases there never mention personal info there, like gender or ethnicity anonymous people are sometimes racist, and you can't do much about it
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