We live in the age of the algorithm. Increasingly, the decisions that affect our lives--where we go to school, whether we can get a job or a loan, how much we pay for health insurance--are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.
But as mathematician and data scientist Cathy O'Neil reveals, the mathematical models being used today are unregulated and uncontestable, even when they're wrong. Most troubling, they reinforce discrimination--propping up the lucky, punishing the downtrodden, and undermining our democracy in the process.

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 urgent and necessary 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 zip code), 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, O'Neil exposes the black box models that shape our future, both as individuals and as a society. These "weapons of math destruction" score teachers and students, sort résumés, grant (or deny) loans, evaluate workers, target voters, set parole, and monitor our health.
O'Neil calls on modelers to take more responsibility for their algorithms and on policy makers to regulate their use. 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.
-- Longlist for National Book Award (Non-Fiction)
-- Goodreads, semi-finalist for the 2016 Goodreads Choice Awards (Science and Technology)
-- Kirkus, Best Books of 2016
-- New York Times, 100 Notable Books of 2016 (Non-Fiction)
-- The Guardian, Best Books of 2016
-- WBUR's "On Point," Best Books of 2016: Staff Picks
-- Boston Globe, Best Books of 2016, Non-Fiction

Now that answering complex and compelling questions with data can make the difference in an election or a business model, data science is an attractive discipline. But how can you learn this wide-ranging, interdisciplinary field? With this book, you’ll get material from Columbia University’s "Introduction to Data Science" class in an easy-to-follow format.
Each chapter-long lecture features a guest data scientist from a prominent company such as Google, Microsoft, or eBay teaching new algorithms, methods, or models by sharing case studies and actual code they use. You’ll learn what’s involved in the lives of data scientists and be able to use the techniques they present.
Guest lectures focus on topics such as:
Machine learning and data mining algorithms
Statistical models and methods
Prediction vs. description
Exploratory data analysis
Communication and visualization
Data processing
Big data
Programming
Ethics
Asking good questions
If you’re familiar with linear algebra, probability and statistics, and have some programming experience, this book will get you started with data science.
Doing Data Science is collaboration between course instructor Rachel Schutt (also employed by Google) and data science consultant Cathy O’Neil (former quantitative analyst for D.E. Shaw) who attended and blogged about the course.

We live in the age of the algorithm. Increasingly, the decisions that affect our lives--where we go to school, whether we can get a job or a loan, how much we pay for health insurance--are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.
But as mathematician and data scientist Cathy O'Neil reveals, the mathematical models being used today are unregulated and uncontestable, even when they're wrong. Most troubling, they reinforce discrimination--propping up the lucky, punishing the downtrodden, and undermining our democracy in the process.

A clear-eyed warning about the increasingly destructive influence of America’s “shame industrial complex” in the age of social media and hyperpartisan politics—from the New York Times bestselling author of Weapons of Math Destruction

Shame is a powerful and sometimes useful tool: When we publicly shame corrupt politicians, abusive celebrities, or predatory corporations, we reinforce values of fairness and justice. But as Cathy O’Neil argues in this revelatory book, shaming has taken a new and dangerous turn. It is increasingly being weaponized—used as a way to shift responsibility for social problems from institutions to individuals. Shaming children for not being able to afford school lunches or adults for not being able to find work lets us off the hook as a society. After all, why pay higher taxes to fund programs for people who are fundamentally unworthy?

O’Neil explores the machinery behind all this shame, showing how governments, corporations, and the healthcare system capitalize on it. There are damning stories of rehab clinics, reentry programs, drug and diet companies, and social media platforms—all of which profit from “punching down” on the vulnerable. Woven throughout The Shame Machine is the story of O’Neil’s own struggle with body image and her recent decision to undergo weight-loss surgery, shaking off decades of shame.

With clarity and nuance, O’Neil dissects the relationship between shame and power. Whom does the system serve? Is it counter-productive to call out racists, misogynists, and vaccine skeptics? If so, when should someone be “canceled”? How do current incentive structures perpetuate the shaming cycle? And, most important, how can we all fight back?

Bem-vindo ao outro lado do Big Data. – Best Seller do New York Times – Indicado ao National Book Award – "Um manual para o cidadão do século XXI… Relevante e urgente." ― Financial Times "O livro de Cathy O'Neil oferece um olhar assustador sobre como os algoritmos estão regulando as pessoas. Seu conhecimento do poder e dos riscos dos modelos matemáticos, juntamente com o dom da analogia, torna-a uma das mais valiosas observadoras da contínua ameaça do Big Data." ― The New York Times Vivemos na Era do Algoritmo. Cada vez mais, as decisões que afetam nossas vidas ― onde estudamos, se obtemos um empréstimo para comprar um carro, quanto pagamos pelo seguro saúde ― estão sendo tomadas por modelos matemáticos. Em teoria, isso deveria nos conduzir para um mundo mais todos são julgados de acordo com as mesmas regras e o preconceito é eliminado. Mas, como Cathy O'Neil revela neste livro urgente e necessário, a verdade é justamente o contrário. Os modelos usados hoje são opacos, não regulamentados e incontestáveis, mesmo quando estão errados. Cathy O'NeilO mais preocupante é que eles reforçam a discriminaçã se um estudante pobre não consegue obter um empréstimo porque o modelo matemático o considera muito arriscado (graças ao endereço onde mora), ele também é recusado na universidade que poderia tirá-lo da pobreza. Os algoritmos criam uma espiral discriminatória. Os modelos amparam os privilegiados e punem os oprimidos, criando um "coquetel tóxico para a democracia".