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I urge you to read this important, nuanced, smart piece in @techreview by @_KarenHao about what went down last week with @timnitGebru.
The researchers' concerns are exactly what I wrote about in my book on AI's problems The Big Nine.
Short thread... https://www.technologyreview.com/2020/12/04/1013294/google-ai-ethics-research-paper-forced-out-timnit-gebru/
The researchers' concerns are exactly what I wrote about in my book on AI's problems The Big Nine.
Short thread... https://www.technologyreview.com/2020/12/04/1013294/google-ai-ethics-research-paper-forced-out-timnit-gebru/
Through one of the paper's authors, @_KarenHao -- who herself was a researcher and is a graduate of MIT -- reviewed the paper that forced @timnitGebru out of Google last week.
Karen knows her stuff, and I trust her understanding and interpretation of complex research.
Karen knows her stuff, and I trust her understanding and interpretation of complex research.
For those who are still fixated on the future when robots coming to take all our jobs and then murdering us, you should know that the real danger posed by AI is already here. It's a concentration of power within just a handful of companies making decisions for us all.
This is boring but important: the people selecting which data to use to train their models wield TREMENDOUS power in our everyday lives.
That's why @timnitGebru and her colleagues' work is vitally important.
That's why @timnitGebru and her colleagues' work is vitally important.
There are many people raising concerns about the data used to train models –– and the ultimate purpose of those models in society.
@timnitGebru @jovialjoy and others are using next-order thinking. It's necessary, but often not a part of the R&D roadmap at GMAFIA companies.
@timnitGebru @jovialjoy and others are using next-order thinking. It's necessary, but often not a part of the R&D roadmap at GMAFIA companies.
(GMAFIA and the BAT make up the Big Nine AI companies: Google, Microsoft, Amazon, Facebook, IBM, Apple, Baidu, Alibaba, Tencent.)
The problems in AI aren't a Black issue, or a woman issue, or an issue singularly confined to one group. Our problems are *humanity's* problems. The seeds were sewn in the 1950s by a homogenous group of men who framed today's understanding of AI.
At this point, we should acknowledge that Wikipedia is the least of our troubles.
Reddit -- yes, that reddit -- is a set of data used to train language and other models.
Reddit -- yes, that reddit -- is a set of data used to train language and other models.
Do not discount @timnitGebru @jovialjoy @safiyanoble @rajiinio @merbroussard @mathbabedotorg and others who are painstakingly researching and writing about AI problems simply because they don't look like you.
We have a global-scale problem in progress affecting ALL OF US.
We have a global-scale problem in progress affecting ALL OF US.
In sum:
1. Read @_KarenHao's excellent piece in @techreview.
2. Then revisit @timnitGebru's email and tweets.
3. Then read Jeff's response.
</> https://www.technologyreview.com/2020/12/04/1013294/google-ai-ethics-research-paper-forced-out-timnit-gebru/
1. Read @_KarenHao's excellent piece in @techreview.
2. Then revisit @timnitGebru's email and tweets.
3. Then read Jeff's response.
</> https://www.technologyreview.com/2020/12/04/1013294/google-ai-ethics-research-paper-forced-out-timnit-gebru/
