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Reviews for Weapons of Math Destruction
September 7, 2016
The reviews are coming in of my new book, Weapons of Math Destruction (also available as an audiobook, which I read myself! (clip here)). Here are some of them:
- Weapons of Math Destruction: invisible, ubiquitous algorithms are ruining millions of lives by Cory Doctorow from his blog Boingboing.net
- Weapons of Math Destruction by Peter Woit from his blog, Not Even Wrong
- Big Data Isn’t Just Watching You—It’s Making You Poorer by Pankaj Mehta on the site In These Times
- Review: Weapons of Math Destruction by Evelyn Lamb in Scientific American
- Math is racist: How data is driving inequality by Aimee Rawlins on CNN Money. Note: I would not have chosen this title, since I’m not claiming math is racist, but rather that some potentially discriminatory practices are being shielded by mathematics. I should note that journalists don’t always choose their own titles, and I think Aimee did a good job with the content of the article
- On Cathy O’Neil’s Weapons of Math Destruction by Chris Hoofnagle, on his blog at the UC Berkeley Law School
- Math Is Biased Against Women and the Poor, According to a Former Math Professor by Priya Rao on NYMag’s The Cut
There may be more I’m missing, please send me links! The coverage has been fantastic, and I’m super excited for the coming weeks and months as we finally get to discuss these issues.
Also, I’d like to urge you all to review my book on Amazon when you get a chance. The book is controversial and a few negative reviews can drag down the average pretty quickly. Having said that, please be completely honest of course!
Here’s my favorite graphic, from CNN:
Categories: Uncategorized
mathbabe 
Also covered in Books in Brief section of Nature last week (http://www.nature.com/nature/journal/v537/n7618/full/537033a.html)
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Algorithmic overlords. Cool.
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Something I’ve grappled with since I heard the study about the recidivism algorithms being “racist” is this:
If we don’t use race as a predictor and it turns out the model is “racist” does that mean we should use race as a input?
Similar question: What if a given recidivism model turned out to under-predict minority recidivism without using race as a predictor. should race be added more-or-less knowing minority variables will be tied to positive coefficients?
Sorry if you’ve answered these before, I came around thanks to the (as you mentioned) poorly-titled and well-written “Is Math Racist?” article.
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Let’s say that you include race as a predictor when estimating the model, but when you compute the predictions set everyones race to white. Shouldn’t the predictions then be non-racist in the sense that it only predicts variation in the response that is not a direct consequence of race.
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Conferring white privilege on everyone. Interesting idea.
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I want to be honest and tell you that I did read an article that said “math was racist” and automatically shut off. but… I then read some of the excerpts and realized it was the application of the math, right? I think headlines saying “math is racist” will turn people off… I hope it doesn’t you are obviously quite intelligent. I think “racist” is used way too often, and incorrectly, and here it seems more about human error, or parameters that were given may have racist leanings, but not the actual math.
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I did a Google search and even up to page 10, there’s a lot of activity, and I realize that some of the links go back to your video of the same name, but it’s all looking good. There was a link at the Daily Koz but when I looked at it, the story had been removed, some gutless writer of a blog post maybe…lol.
Look at this nonsense from Bloomberg now…
“Wall Street’s Next Frontier Is Hacking Into Emotions of Traders”. Hey now that’s a real solid basis for buying and selling stocks…not:) This looks more like “fake” WMDs just for profit:)
http://www.bloomberg.com/news/articles/2016-09-01/wall-street-s-next-frontier-is-hacking-into-emotions-of-traders?utm_content=businessweek&cmpid=socialflow-twitter-businessweek&utm_campaign=socialflow-organic&utm_source=twitter&utm_medium=social
I’m doing my best promoting on Twitter to the healthcare crowd with your book!
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CJ Cherryh shared the CNN Money review on FB. (I think you can see it if you “follow” her there.) Lots of comments so far.
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Hi Cathy
Thanks for the great book.
Here’s a review from my blog.
http://paulamery.net/2016/09/07/the-hidden-dangers-of-big-data/
Kind regards
Paul
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Mentioned by Matt Levine, Bloomberg columnist:
And elsewhere in alienating algorithms, Cathy O’Neil’s book “Weapons of Mass Destruction” just came out, and is very good — the unusual book that changed my mind about things.
https://www.bloomberg.com/view/articles/2016-09-08/apple-fiction-and-robot-hiring
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Mentioned in Matt Levine’s Money Stuff, a Bloomberg column:
And elsewhere in alienating algorithms, Cathy O’Neil’s book “Weapons of Mass Destruction” just came out, and is very good — the unusual book that changed my mind about things.
https://www.bloomberg.com/view/articles/2016-09-08/apple-fiction-and-robot-hiring
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Hey! It’s hard to change Matt’s mind, I’m very proud.
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Just heard an ad for the book on NPR’s Morning Edition. The Big Time!
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Found this over at American Banker…”Did Someone Say Chief Data Officer?”…a paragraph
http://www.americanbanker.com/bankthink/women-in-banking-is-big-data-a-weapon-of-mass-discrimination-1091187-1.html
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Another review I saw at https://www.insidehighered.com/blogs/library-babel-fish/weapons-math-destruction-dark-side-big-data The conclusion: “For anyone who cares about information systems and how society works these days, it’s a must read.”
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Cathy, I haven’t read your book yet but I did see you on C-Span Book TV and all I could think was Thank God! somebody is focusing on the impact of these systems. I’m not a mathematician but I didn’t need to be to know how this data was being used. I worked on large scale corporate information systems so I know how they can be used to control people and processes. I had my ‘Come to Jesus’ moment sometime in 2005 when I read a conceptual design for a national labor management system that included integrated school and work history. As I looked at the student information that was being collected and the movement towards “assessment” rather than objective test scores, I knew what the future held and I’ve been trying to sound the alarms ever since. What you are doing is vitally important and regardless of what feedback you get on your book, push on because you are on the right track.
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