Weapons of Math Destruction

Weapons of Math Destruction

How Big Data Increases Inequality and Threatens Democracy

eBook - 2016
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A former Wall Street quantitative analyst sounds an alarm on mathematical modeling, a pervasive new force in society that threatens to undermine democracy and widen inequality.
Publisher: New York :, Crown,, [2016]
Edition: First edition
ISBN: 9780553418828
0553418823
Characteristics: 1 online resource (x, 259 pages)
Alternative Title: Axis 360 eBooks

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s
ScienceMommy
Jul 31, 2017

OMG!
.
The author is cogent, extremely engaging and writes in a way that draws you in and makes continuing on effortless...as she educates you about what is going on and gives real life examples of how critical things get delegated to computers and algorithms -- but often have unintended consequences -- that are unjust and or cause very real harms to real people. But as any of you know -- actually finding and being able to engage a REAL person at some company or government agency can be difficult -- and then when you finally do, the odds are -- they don't have the power or ability to do anything about it.

Whether its about credit, health care, the Affordable Care Act, being hired for a job, increasingly rigid algorithms based upon, "proxy" (something picked to approximate something that might be hard to assess or measure --- and therefore WRONG!) are determining outcomes -- and we never know, let alone have any ability to challenge these decisions. What's worse -- is the errors serve to reinforce and exacerbate already existing injustices in our society (like race and other forms of systemic privilege)

They used to say, "You can't fight city hall..." But that was child's play compared to trying to fight an algorithm -- even worse, most of the time, you will never know that your bad fortune was in fact CAUSED by an unjust algorithm.
.

Read this book -- along with, "The New Jim Crow" and you will really have a much better understanding of the challenges that if not addressed threaten to unravel quality of life in the US for everyone.

g
Gung
Jul 23, 2017

This is an interesting read for someone in his/her seventh decade (i.e. me) and a must read for someone in their third, fourth and fifth decade. It’s always important to understand what you are up against. (There is likely an algorithm monitoring these comments.)

JCLChrisK May 26, 2017

You are prey. The predator is numbers. Numbers that have been carefully designed to turn you into prey. Numbers wielded by marketers, politicians, insurance companies, and so many others. The problem with these particular numbers is that they give those using them the illusion of knowing you when all they really manage is a proxy, a mathematical approximation that may or may not be accurate. And they are built into self-feeding, self-affirming, reinforcing loops that make them ever more restrictive and controlling. They don't simply feed on us, they increasingly define us.

Cathy O'Neil has been a mathematics professor and has worked in the data science industry in a variety of businesses and roles. She knows how the numbers work and has seen them in action from multiple perspectives. At the start of her conclusion in Weapons of Math Destruction, she writes:

"In this march through a virtual lifetime, we’ve visited school and college, the courts and the workplace, even the voting booth. Along the way, we’ve witnessed the destruction caused by WMDs. Promising efficiency and fairness, they distort higher education, drive up debt, spur mass incarceration, pummel the poor at nearly every juncture, and undermine democracy. It might seem like the logical response is to disarm these weapons, one by one.

"The problem is that they’re feeding on each other. Poor people are more likely to have bad credit and live in high-crime neighborhoods, surrounded by other poor people. Once the dark universe of WMDs digests that data, it showers them with predatory ads for subprime loans or for-profit schools. It sends more police to arrest them, and when they’re convicted it sentences them to longer terms. This data feeds into other WMDs, which score the same people as high risks or easy targets and proceed to block them from jobs, while jacking up their rates for mortgages, car loans, and every kind of insurance imaginable. This drives their credit rating down further, creating nothing less than a death spiral of modeling. Being poor in a world of WMDs is getting more and more dangerous and expensive.

"The same WMDs that abuse the poor also place the comfortable classes of society in their own marketing silos. . . . The quiet and personal nature of this targeting keeps society’s winners from seeing how the very same models are destroying lives, sometimes just a few blocks away."

O'Neil has crafted a broad overview that introduces the complexity of the topic with numerous examples, and through it a call to wield those tools more ethically and morally. The book is highly accessible, intelligent without being difficult and entertaining without being frivolous. This is a book that deserves high readership and a topic that needs extensive discussion.

"Predictive models are, increasingly, the tools we will be relying on the run our institutions, deploy our resources, and manage our lives. But as I’ve tried to show throughout this book, these models are constructed not just from data but from the choices we make about which data to pay attention to—and which to leave out. Those choices are not just about logistics, profits, and efficiency. They are fundamentally moral."

r
RBVanDyke
Feb 20, 2017

Even if one has some amount of math skills -- let's say some algebra, geometry, and perhaps a bit of calculus -- a maths doctorate will try to shut down any arguments by resorting to esoteric mathematical concepts: "You don't know this abstruse aspect of maths, therefore you're not qualified to express doubts about the objectivity of our algorithms."

How informative, then, to have a Harvard PhD in maths with both academic and business experience debunk the self-proclaimed objectivity of mathematics. Among other revelations, Dr. O'Neil points out the insidious nature of self-reinforcing applications of "objective" mathematics that end up portraying a very distorted version of events.

Definitely a must-read for those who perceive mathematically minded technologists supplanting theologians as self-proclaimed holders of The One and Only Truth...

m
masonrobert068
Feb 09, 2017

In the current political and technological moment,
I can't imagine a more important book than this.
The author - mathematician, investment software
technician, and social critic - opened my eyes to
the profound and multiple ways that the internet's
discovery and exploitation of big data, especially
personal preference & behavior data, change the
fabric of social and economic and political reality
in the world, radically, and right now.

g
GummiGirl
Dec 01, 2016

A useful compendium of various common algorithms and their limitations. Although many of these are already well known, the author ties them together effectively with her central thesis: they are all contributing to inequality.

VaughanPLKasey Nov 15, 2016

A thorough, timely, and accessible explanation of the ways in which supposedly 'neutral' mathematical algorithms and models can very easily be misused in ways that further entrench systemic inequalities and biases.

s
StarGladiator
Sep 12, 2016

Really! The bottom paragraph on p. 2 might just dissuade many from finishing this, but I did anyway. In her past experience with D.E. Shaw [employer of Larry Summers, and involved with some highly suspicious backdoor machinations involving the original Bank of America and Russian bonds back in the 1990s, whereby BofA was taken over by Nation's Bank, which is really what BofA is today] the author makes specious remarks like // hedge funds hedge \\ - - author may wish to consult CFTC study instigated by Gary Gensler, which indicated they primarily speculate, although many also act as unofficial [and unregulated] banks, lending to others after due diligence of their books, which they then utilize in trades and investments, et cetera, plus internalization, of course, which is where the top banks and hedge funds buy up over 95% of the public trades from the major brokerages and perform said trades themselves, furthering their command and control of the stock markets and insider trading.
Book should have been published as a lengthy article, author's premise isn't really concrete enough.

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JCLChrisK May 26, 2017

Models, despite their reputation for impartiality, reflect goals and ideology. . . . It’s something we do without a second thought. Our own values and desires influence our choices, from the data we choose to collect to the questions we ask. Models are opinions embedded in mathematics.

JCLChrisK May 26, 2017

Big Data processes codify the past. They do not invent the future. Doing that requires moral imagination, and that’s something only humans can provide. We have to explicitly embed better values into our algorithms, creating Big Data models that follow our ethical lead. Sometimes that will mean putting fairness ahead of profit.

JCLChrisK May 26, 2017

We’ve seen time and again that mathematical models can sift through data to locate people who are likely to face great challenges, whether from crime, poverty, or educations. It’s up to society whether to use that intelligence to reject and punish them—or to reach out to them with the resources they need. We can use the scale and efficiency that make WMDs so pernicious in order to help people. It all depends on the objective we choose.

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