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Weapons of Math Destruction: How Big Data…

Weapons of Math Destruction: How Big Data Increases Inequality and… (2016)

by Cathy O'Neil

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O'Neil takes us on a journey through life, and explains how big data, although useful in many capacities, can be detrimental to the lives of many people such as low income, minorities, and the mentally ill. A main take away is that for big data models to be successful there needs to be continuous "smart" evolution of models using data gathered overtime, and an acknowledgment that there can be harm done to some segments of the population. This was well worth the read, and something I would suggest to those interested in the implications of big data on society. ( )
  Nanerz | Jul 5, 2017 |
Great overview of all the ways analytics are being used in wide variety of cases, from teacher ratings to targeted ads to what one sees in their Facebook feed. I knew or was aware of some of the areas weapons of math destruction are used, but wasn't aware of how, exactly, other than a general "oh, yeah, Facebook/Google is probably tracking that." E.g., I was completely unaware of how chain stores have used analytics for scheduling shifts and had never heard of "clopening." I was reminded of David Halberstam's The Best and the Brightest and how McNamara and the Whiz Kids relied so much on operations research. Unfortunately, most of these WMDs are proprietary, so a real deep-dive is impossible.

I also highly recommend the author's blog, mathbabe.org. ( )
  encephalical | Jun 11, 2017 |
Too ranty to be of much use, despite there being some value in the message. Just listen to the interview on Econtalk and you'll get all you need. ( )
  jvgravy | May 15, 2017 |
Excellent repudiation of the prevailing ideology/religion of dataism. Its limitations and dangers. The stories presented here are not anecdotal or edge-case, they are central and impact nearly all of us. Dataism is seductive and the fault is usually not with the mathematicians or programmers, but management who wields them in ways they don't understand. The solution is to have a balance of algorithm and humans, with semi-automated systems helping decision makers. This is already happening with some robo-trader products that are a mix of algo and human. Regardless this issue will continue to grow and likely lead to a backlash at some point in the future as we continue to work out how to integrate computers safely into society. ( )
1 vote Stbalbach | Feb 1, 2017 |
upsetting, not surprising. ( )
  weeta | Jan 27, 2017 |
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Amazon.com Product Description (ISBN 0553418815, Hardcover)

A former Wall Street quant sounds an alarm on mathematical modeling—a pervasive new force in society that threatens to undermine democracy and widen inequality.
We live in the age of the algorithm. Increasingly, the decisions that affect our lives—where we go to school, whether we get a car loan, how much we pay for health insurance—are being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: Everyone is judged according to the same rules, and bias is eliminated. But as Cathy O’Neil reveals in this shocking book, the opposite is true. The models being used today are opaque, unregulated, and uncontestable, even when they’re wrong. Most troubling, they reinforce discrimination: If a poor student can’t get a loan because a lending model deems him too risky (by virtue of his race or neighborhood), he’s then cut off from the kind of education that could pull him out of poverty, and a vicious spiral ensues. Models are propping up the lucky and punishing the downtrodden, creating a “toxic cocktail for democracy.” Welcome to the dark side of Big Data.
Tracing the arc of a person’s life, from college to retirement, O’Neil exposes the black box models that shape our future, both as individuals and as a society. Models that score teachers and students, sort resumes, grant (or deny) loans, evaluate workers, target voters, set parole, and monitor our health—all have pernicious feedback loops. They don’t simply describe reality, as proponents claim, they change reality, by expanding or limiting the opportunities people have. O’Neil calls on modelers to take more responsibility for how their algorithms are being used. But in the end, it’s up to us to become more savvy about the models that govern our lives. This important book empowers us to ask the tough questions, uncover the truth, and demand change.

(retrieved from Amazon Fri, 15 Apr 2016 20:07:53 -0400)

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