Search results for: automating-inequality

Automating Inequality

Author : Virginia Eubanks
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WINNER: The 2018 McGannon Center Book Prize and shortlisted for the Goddard Riverside Stephan Russo Book Prize for Social Justice 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.

Automating Inequality

Author : Virginia Eubanks
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"Eubanks ... investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America"--Amazon.com.

Automating Inequality

Author : Virginia Eubanks
File Size : 47.2 MB
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"Eubanks ... investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America"--Amazon.com.

Automating the News

Author : Nicholas Diakopoulos
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From hidden connections in big data to bots spreading fake news, journalism is increasingly computer-generated. Nicholas Diakopoulos explains the present and future of a world in which algorithms have changed how the news is created, disseminated, and received, and he shows why journalists--and their values--are at little risk of being replaced.

Counting How We Use Numbers to Decide What Matters

Author : Deborah Stone
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“Deborah Stone’s mind-altering insight is that the numbers we use to capture the human experience are themselves a form of creative story-telling. They shouldn’t end the conversation, but spark a deeper and richer one. Counting deserves five stars for showing why five stars can never tell the whole story.” —Jacob S. Hacker, co-author of Let Them Eat Tweets: How the Right Rules in an Age of Extreme Inequality What do people do when they count? What do numbers really mean? We all know that people can lie with statistics, but in this groundbreaking work, eminent political scientist Deborah Stone uncovers a much deeper problem. With help from Dr. Seuss and Cookie Monster, she explains why numbers can’t be objective: in order to count, one must first decide what counts. Every number is the ending to a story built on cultural assumptions, social conventions, and personal judgments. And yet, in this age of big data and metric mania, numbers shape almost every facet of our lives: whether we get hired, fired, or promoted; whether we get into college or out of prison; how our opinions are gathered and portrayed to politicians; or how government designs health and safety regulations. In warm and playful prose, Counting explores what happens when we measure nebulous notions like merit, race, poverty, pain, or productivity. When so much rides on numbers, they can become instruments of social welfare, justice, and democracy—or not. The citizens of Flint, Michigan, for instance, used numbers to prove how their household water got contaminated and to force their government to take remedial action. In stark contrast, the Founding Fathers finessed an intractable conflict by counting each slave as three-fifths of a person in the national census. They set a terrible precedent for today’s politicians who claim to solve moral and political dilemmas with arithmetic. Suffused with moral reflection and ending with a powerful epilogue on COVID-19’s dizzying statistics, Counting will forever change our relationship with numbers.

Ethics of Artificial Intelligence

Author : S. Matthew Liao
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"Featuring seventeen original essays on the ethics of Artificial Intelligence (AI) by some of the most prominent AI scientists and academic philosophers today, this volume represents the state-of-the-art thinking in this fast-growing field and highlights some of the central themes in AI and morality such as how to build ethics into AI, how to address mass unemployment as a result of automation, how to avoiding designing AI systems that perpetuate existing biases, and how to determine whether an AI is conscious. As AI technologies progress, questions about the ethics of AI, in both the near-future and the long-term, become more pressing than ever. Should a self-driving car prioritize the lives of the passengers over the lives of pedestrians? Should we as a society develop autonomous weapon systems that are capable of identifying and attacking a target without human intervention? What happens when AIs become smarter and more capable than us? Could they have greater than human moral status? Can we prevent superintelligent AIs from harming us or causing our extinction? At a critical time in this fast-moving debate, thirty leading academics and researchers at the forefront of AI technology development come together to explore these existential questions, including Aaron James (UC Irvine), Allan Dafoe (Oxford), Andrea Loreggia (Padova), Andrew Critch (UC Berkeley), Azim Shariff (Univ. of British Columbia), Carrick Flynn (Oxford), Cathy O'Neil (O'Neil Risk Consulting & Algorithmic Auditing), Eliezer Yudkowsky (Machine Intelligence Research Institute), Eric Schwitzgebel (UC Riverside), Frances Kamm (Rutgers), Francesca Rossi (IBM), Hanna Gunn (UC Merced), Iyad Rahwan (MIT), Jessica Taylor (Median Group), JF Bonnefon (Centre National de la Recherche Scientifique), K. Brent Venable (Tulane), Kate Devlin (King's College London), Mara Garza (UC Riverside), Nicholas Mattei (Tulane), Nick Bostrom (Oxford), Patrick LaVictoire (Lyft), Peter Asaro (The New School), Peter Railton (Michigan), S. Matthew Liao (NYU), Shannon Vallor (Santa Clara), Stephen Wolfram (Wolfram Research), Steve Petersen (Niagara), Stuart Russell (UC Berkeley), Susan Schneider (Univ. of Connecticut), Wendell Wallach (Yale)"--

Automating Social Inequality

Author : KRYSTLE. MAKI
File Size : 62.30 MB
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Inequalities

Author : Michael J. Cloud
File Size : 23.29 MB
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This book offers a concise introduction to mathematical inequalities for graduate students and researchers in the fields of engineering and applied mathematics. It begins by reviewing essential facts from algebra and calculus and proceeds with a presentation of the central inequalities of applied analysis, illustrating a wide variety of practical applications. The text provides a gentle introduction to abstract spaces, such as metric, normed and inner product spaces. It also provides full coverage of the central inequalities of applied analysis, such as Young's inequality, the inequality of the means, Hölder's inequality, Minkowski's inequality, the Cauchy–Schwarz inequality, Chebyshev's inequality, Jensen's inequality and the triangle inequality. The second edition features extended coverage of applications, including continuum mechanics and interval analysis. It also includes many additional examples and exercises with hints and full solutions that may appeal to upper-level undergraduate and graduate students, as well as researchers in engineering, mathematics, physics, chemistry or any other quantitative science.

Automating New York City and Encoding Inequality

Author : Akina Younge
File Size : 23.56 MB
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Automating Interaction

Author : Myles Alexander Ruggles
File Size : 32.11 MB
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This volume traces the history of knowledge, information, and cognate categories as variables in economic thought, from their first appearance in early classical economics, through their place in neo-classical, institutional, and neo-institutional economics, to their role in contemporary investigations in economic psychology. It argues that revision of the methodological assumptions of mainstream economics are necessary to capturing and modeling accurately the welfare implications of information technology innovation and design and adoption process in society.

Thirty Five Years of Automating Mathematics

Author : F.D. Kamareddine
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THIRTY FIVE YEARS OF AUTOMATING MATHEMATICS: DEDICATED TO 35 YEARS OF DE BRUIJN'S AUTOMATH N. G. de Bruijn was a well established mathematician before deciding in 1967 at the age of 49 to work on a new direction related to Automating Mathematics. By then, his contributions in mathematics were numerous and extremely influential. His book on advanced asymptotic methods, North Holland 1958, was a classic and was subsequently turned into a book in the well known Dover book series. His work on combinatorics yielded influential notions and theorems of which we mention the de Bruijn-sequences of 1946 and the de Bruijn-Erdos theorem of 1948. De Bruijn's contributions to mathematics also included his work on generalized function theory, analytic number theory, optimal control, quasicrystals, the mathematical analysis of games and much more. In the 1960s de Bruijn became fascinated by the new computer technology and as a result, decided to start the new AUTOMATH project where he could check, with the help of the computer, the correctness of books of mathematics. In each area that de Bruijn approached, he shed a new light and was known for his originality and for making deep intellectual contributions. And when it came to automating mathematics, he again did it his way and introduced the highly influential AUTOMATH. In the past decade he has also been working on theories of the human brain.

Modern Methods for Automating Finite Element Mesh Generation

Author : Kenneth Baldwin
File Size : 74.53 MB
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Very Good,No Highlights or Markup,all pages are intact.

Working Notes from the 1992 AAAI Workshop on Automating Software Design Theme Domain Specific Software Design

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Automating Specification based Software Testing

Author : Robert M. Poston
File Size : 40.86 MB
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Fundamentals; Test generation; Test execution; Test evaluation; Software testing tools; Appendixes.

Advances in Design Automation 1989 Computer aided and computational Design

Author : Bahram Ravani
File Size : 68.14 MB
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Automating Decision Guidance

Author : Moez Limayem
File Size : 76.11 MB
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Automation and Remote Control

Author :
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Automating Software Design

Author : Michael Randolph Lowry
File Size : 30.45 MB
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The contributions in Automating Software Design provide substantial evidence that AI technology can meet the requirements of the large potential market that will exist for knowledge-based software engineering at the turn of the century. They are divided into sections covering knowledge-based tools for large software systems, knowledge-based specification acquisition, domain-oriented program synthesis, knowledge compilation, knowledge-based program optimization, formal derivation systems, and cognitive and planning approaches to software design. Michael Lowry is at the Kestrel Institute. Robert McCartney is in the Department of Computer Science and Engineering at the University of Connecticut. Partial Contents: Knowledge-Based Software Engineering: How and Why Did We Get Here? The Evolution of Very Large Information Systems. LaSSIE: A knowledge-Based Software Information System. Reducing the Complexity of Formal Specification Acquisition. Software Reuse and Refinement in the IDeA and ROSE Systems. Data Relationships and Software Design. Scientific Programming by Automated Synthesis. Synthesizing VLSI Routing Software from Specification. A Divide-and-Conquer Approach to Knowledge Compilation (the KBSDE project). Program Improvement by Automatic Redistribution of Intermediate Results: An Overview. Concurrent Software Production. Design Principles for an Interactive Program Derivation System. The Structure and Design of Local Search Algorithms. Automating Algorithm Design Within a General Architecture for Intelligence. Software Engineering in the Twenty-First Century.

Inequality com

Author : Kieron O'Hara
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A cautionary analysis of the issues related to the Internet age seeks to balance its potential with an awareness of the Web's role in social inequality and national security, in an account that proposes practical modifications that can apply existing political theories to the regulation of cyberspace.

Urban Income Inequality

Author : Richard Child Hill
File Size : 22.30 MB
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