Andrew A Beveridge (@AABeveridge) profile picture

Professor, Demographer, Social Explorer Developer.

New York City
Joined April 2009
A few years ago, the US Census Bureau adopted a controversial method for maintaining the privacy of personal data, Differential Privacy. Now it turns out that the rationale for doing so was unfounded, amazing story, tinyurl.com/mr4b7uas
He just put up a full blown analysis: Kansas Result Suggests 4 Out of 5 States Would Back Abortion Rights in Similar Vote The referendum in a reliably Republican state shows which party has the most energy on the issue. Full article with a Map here :nytimes.com/2022/08/04/upsho…
Replying to @Nate_Cohn
Of course, there are other differences between theses states, but abortion's overperformance in Kansas survives controls for race, education, Evangelicals, etc.
Andrew A Beveridge retweeted
So thrilled yesterday to have an Authors-Meets-Critics session on my new book, w/ great comments from @ProfCandis, Rachel Ann May, & Gloria Cox @SPSAnews! Co-authored w/ Amy Lutz & Lakshmi Jayaram. tcpress.com/parenting-in-pri…. Free ship. w/ code TCP2022 to check it out! @TCPress
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Looks like Yale’s Grand strategy is to do anything to get 6 billion dollars. Yale BA 67; MPhil 71; PhD 73.
NEW: Yale president Peter Salovey issues letter citing Yale's "unwavering commitment to academic freedom." Says he "should have tried harder to improve the situation" w donors that led Beverly Gage, head of the Grand Strategy seminar, to resign... (1/3) president.yale.edu/president…
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Census Data less noisy, but still some issues, privacy not so much: From Krish Muralidhar to figure out the approximate disclosure risk is as follows: But a quick way of trying to figure out the approximate disclosure risk is as follows: Epsilon = 17.14 Exp(Epsilon) = 27784809
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Frank McSherry, one of the inventors of differential privacy "Apple has put some kind of handcuffs on in how they interact with your data," he says. "It just turns out those handcuffs are made out of tissue paper." wired.com/story/apple-differ…
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And given that any increase in Epsilon is exponential, the Census' privacy level is 23 times worse than even Apple's epsilon level. Best I can do for now. Hope it helps. Krish Muralidhar @histdem
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More: In summary, if the article by Garfinkel et al.proves anything, it proves that even for a very small data set, even when a lot of information is released, if simple disclosure prevention techniques are properly applied, reconstructing the data set is practically impossible.
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But I certainly do mean to imply that differential privacy is not the only solution. The Abowd paper says (above the title on the first page): “These attacks on statistical databases are no longer a theoretical danger.” Freudian slip?
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Full analysis. Database Reconstruction is Very Difficult in Practice Krish Muralidhar, University of Oklahoma (krishm@ou.edu)
New analysis by Krish Muralidhar, shows that Abowd Garfinkel paper upon the new DAS is based has fundamental errors. dropbox.com/s/7plwq3mxe6gt5o…