Is there a word for the way both XKCD and The Onion are funnny but in that too-realistic oh-wait kind of way?
pic.twitter.com/9Ty5s462NL
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Hey, Zeynep! Intriguing. Speaking for us non-statistics nerds, I'm finding it hard to follow the logic and argument of this paper. I hope you'll think about writing on this subject in a public-facing article.
Not to mention what happens when you cross two supposedly anonymized databases with entities in common
This is what the work on Differential Privacy is all about, thanks to Cynthia Dwork. Here's a really good explanation:https://www.youtube.com/watch?v=nTs6CEU2QaM …
Book title suggestion: "Sociology Saviors Tame the AI Wolf: How My Department Landed Thousands of Dollars Concern Trolling" 
Reading replies to the original tweet; have you considered writing a book about how to useGoogle? I suspect there’s a market.
Landmark paper. Cited (among many places) where I first learned about the concept: https://dl.acm.org/citation.cfm?id=383392 …
So I learned. It’s usually like this: most of these issues have been studied for decades! Usually the only reason for the “oops” is because it’s inconvenient/less profitable to pay attention to the existing research.
here's some more recent work looking at ML on text in particular: https://arxiv.org/abs/1802.08232 lots to be concerned about re: power dynamics in ML regardless. but it also seems good to push for privacy audits, datasheets, model cards, etc as part of being called "state-of-the-art"pic.twitter.com/SwTStiLKEY
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