Search Results for "weapons-of-math-destruction-how-big-data-increases-inequality-and-threatens-democracy"

Weapons of Math Destruction

Weapons of Math Destruction

How Big Data Increases Inequality and Threatens Democracy

  • Author: Cathy O'Neil
  • Publisher: Broadway Books
  • ISBN: 0553418823
  • Category: Political Science
  • Page: 288
  • View: 7690
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Longlisted for the National Book Award New York Times Bestseller A former Wall Street quant sounds an alarm on the mathematical models that pervade modern life — and threaten to rip apart our social fabric 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

Weapons of Math Destruction

Weapons of Math Destruction

How Big Data Increases Inequality and Threatens Democracy

  • Author: Cathy O'Neil
  • Publisher: Crown Books
  • ISBN: 0553418815
  • Category: Big data
  • Page: 259
  • View: 6199
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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, "--NoveList.

Weapons of Math Destruction

Weapons of Math Destruction

How Big Data Increases Inequality and Threatens Democracy

  • Author: Cathy O'Neil
  • Publisher: Penguin UK
  • ISBN: 0141985429
  • Category: Technology & Engineering
  • Page: 272
  • View: 499
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A former Wall Street quant sounds an alarm on the mathematical models that pervade modern life - and threaten to rip apart our social fabric We live in the age of the algorithm. Increasingly, the decisions that affect our lives - where we go to school, whether we get a loan, how much we pay for 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. And yet, as Cathy O'Neil reveals in this urgent and necessary book, the opposite is true. The models being used today are opaque, unregulated, and incontestable, even when they're wrong. Most troubling, they reinforce discrimination. 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 CVs, grant or deny loans, evaluate workers, target voters, and monitor our health. O'Neil calls on modellers 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.

Doing Data Science

Doing Data Science

Straight Talk from the Frontline

  • Author: Cathy O'Neil,Rachel Schutt
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 144936389X
  • Category: Computers
  • Page: 408
  • View: 5538
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Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.

Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World

Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World

  • Author: Bruce Schneier
  • Publisher: W. W. Norton & Company
  • ISBN: 0393244822
  • Category: Computers
  • Page: 320
  • View: 5117
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“Bruce Schneier’s amazing book is the best overview of privacy and security ever written.”—Clay Shirky “Bruce Schneier’s amazing book is the best overview of privacy and security ever written.”—Clay Shirky Your cell phone provider tracks your location and knows who’s with you. Your online and in-store purchasing patterns are recorded, and reveal if you're unemployed, sick, or pregnant. Your e-mails and texts expose your intimate and casual friends. Google knows what you’re thinking because it saves your private searches. Facebook can determine your sexual orientation without you ever mentioning it. The powers that surveil us do more than simply store this information. Corporations use surveillance to manipulate not only the news articles and advertisements we each see, but also the prices we’re offered. Governments use surveillance to discriminate, censor, chill free speech, and put people in danger worldwide. And both sides share this information with each other or, even worse, lose it to cybercriminals in huge data breaches. Much of this is voluntary: we cooperate with corporate surveillance because it promises us convenience, and we submit to government surveillance because it promises us protection. The result is a mass surveillance society of our own making. But have we given up more than we’ve gained? In Data and Goliath, security expert Bruce Schneier offers another path, one that values both security and privacy. He brings his bestseller up-to-date with a new preface covering the latest developments, and then shows us exactly what we can do to reform government surveillance programs, shake up surveillance-based business models, and protect our individual privacy. You'll never look at your phone, your computer, your credit cards, or even your car in the same way again.

Big Data

Big Data

A Revolution That Will Transform How We Live, Work, and Think

  • Author: Viktor Mayer-Schönberger,Kenneth Cukier
  • Publisher: Houghton Mifflin Harcourt
  • ISBN: 0544002938
  • Category: Business & Economics
  • Page: 240
  • View: 6256
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A revelatory exploration of the hottest trend in technology and the dramatic impact it will have on the economy, science, and society at large. Which paint color is most likely to tell you that a used car is in good shape? How can officials identify the most dangerous New York City manholes before they explode? And how did Google searches predict the spread of the H1N1 flu outbreak? The key to answering these questions, and many more, is big data. “Big data” refers to our burgeoning ability to crunch vast collections of information, analyze it instantly, and draw sometimes profoundly surprising conclusions from it. This emerging science can translate myriad phenomena—from the price of airline tickets to the text of millions of books—into searchable form, and uses our increasing computing power to unearth epiphanies that we never could have seen before. A revolution on par with the Internet or perhaps even the printing press, big data will change the way we think about business, health, politics, education, and innovation in the years to come. It also poses fresh threats, from the inevitable end of privacy as we know it to the prospect of being penalized for things we haven’t even done yet, based on big data’s ability to predict our future behavior. In this brilliantly clear, often surprising work, two leading experts explain what big data is, how it will change our lives, and what we can do to protect ourselves from its hazards. Big Data is the first big book about the next big thing. www.big-data-book.com

Automating Inequality

Automating Inequality

How High-Tech Tools Profile, Police, and Punish the Poor

  • Author: Virginia Eubanks
  • Publisher: St. Martin's Press
  • ISBN: 1466885963
  • Category: Social Science
  • Page: 288
  • View: 1348
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The New York Times Book Review: "Riveting." Naomi Klein: "This book is downright scary." Ethan Zuckerman, MIT: "Should be required reading." Dorothy Roberts, author of Killing the Black Body: "A must-read." Astra Taylor, author of The People's Platform: "The single most important book about technology you will read this year." Cory Doctorow: "Indispensable." A powerful investigative look at data-based discrimination—and how technology affects civil and human rights and economic equity The State of Indiana denies one million applications for healthcare, foodstamps and cash benefits in three years—because a new computer system interprets any mistake as “failure to cooperate.” In Los Angeles, an algorithm calculates the comparative vulnerability of tens of thousands of homeless people in order to prioritize them for an inadequate pool of housing resources. In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect. Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems—rather than humans—control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor. In Automating Inequality, Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile. The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values. This deeply researched and passionate book could not be more timely.

On Being a Data Skeptic

On Being a Data Skeptic

  • Author: Cathy O'Neil
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 1491947241
  • Category: Computers
  • Page: 28
  • View: 4641
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"Data is here, it's growing, and it's powerful." Author Cathy O'Neil argues that the right approach to data is skeptical, not cynical––it understands that, while powerful, data science tools often fail. Data is nuanced, and "a really excellent skeptic puts the term 'science' into 'data science.'" The big data revolution shouldn't be dismissed as hype, but current data science tools and models shouldn't be hailed as the end-all-be-all, either.

Data for the People

Data for the People

How to Make Our Post-Privacy Economy Work for You

  • Author: Andreas Weigend
  • Publisher: Basic Books
  • ISBN: 0465096530
  • Category: Science
  • Page: 272
  • View: 7885
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A long-time chief data scientist at Amazon shows how open data can make everyone, not just corporations, richer Every time we Google something, Facebook someone, Uber somewhere, or even just turn on a light, we create data that businesses collect and use to make decisions about us. In many ways this has improved our lives, yet, we as individuals do not benefit from this wealth of data as much as we could. Moreover, whether it is a bank evaluating our credit worthiness, an insurance company determining our risk level, or a potential employer deciding whether we get a job, it is likely that this data will be used against us rather than for us. In Data for the People, Andreas Weigend draws on his years as a consultant for commerce, education, healthcare, travel and finance companies to outline how Big Data can work better for all of us. As of today, how much we benefit from Big Data depends on how closely the interests of big companies align with our own. Too often, outdated standards of control and privacy force us into unfair contracts with data companies, but it doesn't have to be this way. Weigend makes a powerful argument that we need to take control of how our data is used to actually make it work for us. Only then can we the people get back more from Big Data than we give it. Big Data is here to stay. Now is the time to find out how we can be empowered by it.

What Algorithms Want

What Algorithms Want

Imagination in the Age of Computing

  • Author: Ed Finn
  • Publisher: MIT Press
  • ISBN: 0262035928
  • Category: Computers
  • Page: 257
  • View: 1649
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The gap between theoretical ideas and messy reality, as seen in Neal Stephenson, Adam Smith, and Star Trek. We depend on—we believe in—algorithms to help us get a ride, choose which book to buy, execute a mathematical proof. It's as if we think of code as a magic spell, an incantation to reveal what we need to know and even what we want. Humans have always believed that certain invocations—the marriage vow, the shaman's curse—do not merely describe the world but make it. Computation casts a cultural shadow that is shaped by this long tradition of magical thinking. In this book, Ed Finn considers how the algorithm—in practical terms, “a method for solving a problem”—has its roots not only in mathematical logic but also in cybernetics, philosophy, and magical thinking. Finn argues that the algorithm deploys concepts from the idealized space of computation in a messy reality, with unpredictable and sometimes fascinating results. Drawing on sources that range from Neal Stephenson's Snow Crash to Diderot's Encyclopédie, from Adam Smith to the Star Trek computer, Finn explores the gap between theoretical ideas and pragmatic instructions. He examines the development of intelligent assistants like Siri, the rise of algorithmic aesthetics at Netflix, Ian Bogost's satiric Facebook game Cow Clicker, and the revolutionary economics of Bitcoin. He describes Google's goal of anticipating our questions, Uber's cartoon maps and black box accounting, and what Facebook tells us about programmable value, among other things. If we want to understand the gap between abstraction and messy reality, Finn argues, we need to build a model of “algorithmic reading” and scholarship that attends to process, spearheading a new experimental humanities.

Algorithms to Live By

Algorithms to Live By

The Computer Science of Human Decisions

  • Author: Brian Christian,Tom Griffiths
  • Publisher: Macmillan
  • ISBN: 1627790365
  • Category: Business & Economics
  • Page: 368
  • View: 5156
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A fascinating exploration of how insights from computer algorithms can be applied to our everyday lives, helping to solve common decision-making problems and illuminate the workings of the human mind All our lives are constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favorites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such issues for decades. And the solutions they've found have much to teach us. In a dazzlingly interdisciplinary work, acclaimed author Brian Christian and cognitive scientist Tom Griffiths show how the algorithms used by computers can also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.

Big Data in Education

Big Data in Education

The Digital Future of Learning, Policy and Practice

  • Author: Ben Williamson
  • Publisher: SAGE
  • ISBN: 1526416344
  • Category: Computers
  • Page: 248
  • View: 7519
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This cutting-edge overview explores big data and the related topic of computer code, examining the implications for education and schooling for today and the near future.

Hand to Mouth

Hand to Mouth

Living in Bootstrap America

  • Author: Linda Tirado
  • Publisher: Penguin
  • ISBN: 0425277976
  • Category: Biography & Autobiography
  • Page: 240
  • View: 4235
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Originally published in hardcover in 2014 by G.P. Putnam's Sons.

Algorithms of Oppression

Algorithms of Oppression

How Search Engines Reinforce Racism

  • Author: Safiya Umoja Noble
  • Publisher: NYU Press
  • ISBN: 1479837245
  • Category: Computers
  • Page: 256
  • View: 7531
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A revealing look at how negative biases against women of color are embedded in search engine results and algorithms Run a Google search for “black girls”—what will you find? “Big Booty” and other sexually explicit terms are likely to come up as top search terms. But, if you type in “white girls,” the results are radically different. The suggested porn sites and un-moderated discussions about “why black women are so sassy” or “why black women are so angry” presents a disturbing portrait of black womanhood in modern society. In Algorithms of Oppression, Safiya Umoja Noble challenges the idea that search engines like Google offer an equal playing field for all forms of ideas, identities, and activities. Data discrimination is a real social problem; Noble argues that the combination of private interests in promoting certain sites, along with the monopoly status of a relatively small number of Internet search engines, leads to a biased set of search algorithms that privilege whiteness and discriminate against people of color, specifically women of color. Through an analysis of textual and media searches as well as extensive research on paid online advertising, Noble exposes a culture of racism and sexism in the way discoverability is created online. As search engines and their related companies grow in importance—operating as a source for email, a major vehicle for primary and secondary school learning, and beyond—understanding and reversing these disquieting trends and discriminatory practices is of utmost importance. An original, surprising and, at times, disturbing account of bias on the internet, Algorithms of Oppression contributes to our understanding of how racism is created, maintained, and disseminated in the 21st century.

Algorithms for Data Science

Algorithms for Data Science

  • Author: Brian Steele,John Chandler,Swarna Reddy
  • Publisher: Springer
  • ISBN: 3319457977
  • Category: Computers
  • Page: 430
  • View: 9704
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This textbook on practical data analytics unites fundamental principles, algorithms, and data. Algorithms are the keystone of data analytics and the focal point of this textbook. Clear and intuitive explanations of the mathematical and statistical foundations make the algorithms transparent. But practical data analytics requires more than just the foundations. Problems and data are enormously variable and only the most elementary of algorithms can be used without modification. Programming fluency and experience with real and challenging data is indispensable and so the reader is immersed in Python and R and real data analysis. By the end of the book, the reader will have gained the ability to adapt algorithms to new problems and carry out innovative analyses. This book has three parts:(a) Data Reduction: Begins with the concepts of data reduction, data maps, and information extraction. The second chapter introduces associative statistics, the mathematical foundation of scalable algorithms and distributed computing. Practical aspects of distributed computing is the subject of the Hadoop and MapReduce chapter.(b) Extracting Information from Data: Linear regression and data visualization are the principal topics of Part II. The authors dedicate a chapter to the critical domain of Healthcare Analytics for an extended example of practical data analytics. The algorithms and analytics will be of much interest to practitioners interested in utilizing the large and unwieldly data sets of the Centers for Disease Control and Prevention's Behavioral Risk Factor Surveillance System.(c) Predictive Analytics Two foundational and widely used algorithms, k-nearest neighbors and naive Bayes, are developed in detail. A chapter is dedicated to forecasting. The last chapter focuses on streaming data and uses publicly accessible data streams originating from the Twitter API and the NASDAQ stock market in the tutorials. This book is intended for a one- or two-semester course in data analytics for upper-division undergraduate and graduate students in mathematics, statistics, and computer science. The prerequisites are kept low, and students with one or two courses in probability or statistics, an exposure to vectors and matrices, and a programming course will have no difficulty. The core material of every chapter is accessible to all with these prerequisites. The chapters often expand at the close with innovations of interest to practitioners of data science. Each chapter includes exercises of varying levels of difficulty. The text is eminently suitable for self-study and an exceptional resource for practitioners.

Cities Are Good for You

Cities Are Good for You

The Genius of the Metropolis

  • Author: Leo Hollis
  • Publisher: Bloomsbury Publishing USA
  • ISBN: 1620402076
  • Category: Social Science
  • Page: 304
  • View: 4340
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Cities are where the twenty-first century is really going to happen. Already at the beginning of the century, we became 50% urban as a global population, and by 2050 we're going to be up to 70% urban. So cities could either be our coffin or our ark. Leo Hollis presents evidence that cities can deliver a better life and a better world in the future. From exploring what slime mold can tell us about traffic flow, to looking at how traditional civic power structures are being overturned by Twitter, to investigating how cities all over the world are tackling climate change, population growth, poverty, shifting work patterns and the maintenance of the fragile trust of their citizens, Cities Are Good for You offers a new perspective on the city. Combining anecdote, scientific studies, historical portraits, first-hand interviews and observations of some of the most exciting world cities, Hollis upends long-held assumptions with new questions: Where do cities come from? Can we build a city from scratch? Does living in the city make you happier or fitter? Is the metropolis of the future female? What is the relationship between cities and creativity? And are slums really all that bad? Cities Are Good for You introduces us to dreamers, planners, revolutionaries, writers, scientists, architects, slum-dwellers and kings. Ranging globally and through time in search of answers--from the archive to the laboratory, from City Hall to the architect's desk--it is above all driven by the idea that cities are for people and by people.

The Black Box Society

The Black Box Society

The Secret Algorithms That Control Money and Information

  • Author: Frank Pasquale
  • Publisher: Harvard University Press
  • ISBN: 0674967100
  • Category: Law
  • Page: 319
  • View: 5510
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Every day, corporations are connecting the dots about our personal behavior—silently scrutinizing clues left behind by our work habits and Internet use. But who connects the dots about what firms are doing with all this information? Frank Pasquale exposes how powerful interests abuse secrecy for profit and explains ways to rein them in.

Everybody Lies

Everybody Lies

Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are

  • Author: Seth Stephens-Davidowitz
  • Publisher: HarperCollins
  • ISBN: 0062390872
  • Category: Social Science
  • Page: 352
  • View: 8624
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Foreword by Steven Pinker Blending the informed analysis of The Signal and the Noise with the instructive iconoclasm of Think Like a Freak, a fascinating, illuminating, and witty look at what the vast amounts of information now instantly available to us reveals about ourselves and our world—provided we ask the right questions. By the end of an average day in the early twenty-first century, human beings searching the internet will amass eight trillion gigabytes of data. This staggering amount of information—unprecedented in history—can tell us a great deal about who we are—the fears, desires, and behaviors that drive us, and the conscious and unconscious decisions we make. From the profound to the mundane, we can gain astonishing knowledge about the human psyche that less than twenty years ago, seemed unfathomable. Everybody Lies offers fascinating, surprising, and sometimes laugh-out-loud insights into everything from economics to ethics to sports to race to sex, gender and more, all drawn from the world of big data. What percentage of white voters didn’t vote for Barack Obama because he’s black? Does where you go to school effect how successful you are in life? Do parents secretly favor boy children over girls? Do violent films affect the crime rate? Can you beat the stock market? How regularly do we lie about our sex lives and who’s more self-conscious about sex, men or women? Investigating these questions and a host of others, Seth Stephens-Davidowitz offers revelations that can help us understand ourselves and our lives better. Drawing on studies and experiments on how we really live and think, he demonstrates in fascinating and often funny ways the extent to which all the world is indeed a lab. With conclusions ranging from strange-but-true to thought-provoking to disturbing, he explores the power of this digital truth serum and its deeper potential—revealing biases deeply embedded within us, information we can use to change our culture, and the questions we’re afraid to ask that might be essential to our health—both emotional and physical. All of us are touched by big data everyday, and its influence is multiplying. Everybody Lies challenges us to think differently about how we see it and the world.

Technically Wrong: Sexist Apps, Biased Algorithms, and Other Threats of Toxic Tech

Technically Wrong: Sexist Apps, Biased Algorithms, and Other Threats of Toxic Tech

  • Author: Sara Wachter-Boettcher
  • Publisher: W. W. Norton & Company
  • ISBN: 0393634647
  • Category: Computers
  • Page: 240
  • View: 8734
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A revealing look at how tech industry bias and blind spots get baked into digital products—and harm us all. Buying groceries, tracking our health, finding a date: whatever we want to do, odds are that we can now do it online. But few of us ask why all these digital products are designed the way they are. It’s time we change that. Many of the services we rely on are full of oversights, biases, and downright ethical nightmares: Chatbots that harass women. Signup forms that fail anyone who’s not straight. Social media sites that send peppy messages about dead relatives. Algorithms that put more black people behind bars. Sara Wachter-Boettcher takes an unflinching look at the values, processes, and assumptions that lead to these and other problems. Technically Wrong demystifies the tech industry, leaving those of us on the other side of the screen better prepared to make informed choices about the services we use—and demand more from the companies behind them.

Big Data

Big Data

A Revolution That Will Transform How We Live, Work and Think

  • Author: Viktor Mayer-Schonberger,Kenneth Cukier
  • Publisher: John Murray
  • ISBN: 9781473647206
  • Category:
  • Page: 320
  • View: 1070
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New and expanded edition. An International Bestseller - Over One Million Copies Sold! Longlisted for the Financial Times/Goldman Sachs Business Book of the Year Award. Since Aristotle, we have fought to understand the causes behind everything. But this ideology is fading. In the age of big data, we can crunch an incomprehensible amount of information, providing us with invaluable insights about the what rather than the why. We're just starting to reap the benefits: tracking vital signs to foresee deadly infections, predicting building fires, anticipating the best moment to buy a plane ticket, seeing inflation in real time and monitoring social media in order to identify trends. But there is a dark side to big data. Will it be machines, rather than people, that make the decisions? How do you regulate an algorithm? What will happen to privacy? Will individuals be punished for acts they have yet to commit? In this groundbreaking and fascinating book, two of the world's most-respected data experts reveal the reality of a big data world and outline clear and actionable steps that will equip the reader with the tools needed for this next phase of human evolution.