Discriminating Data
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Discriminating Data
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Author : Wendy Hui Kyong Chun
language : en
Publisher: MIT Press
Release Date : 2021-11-02
Discriminating Data written by Wendy Hui Kyong Chun and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-02 with Technology & Engineering categories.
How big data and machine learning encode discrimination and create agitated clusters of comforting rage. In Discriminating Data, Wendy Hui Kyong Chun reveals how polarization is a goal—not an error—within big data and machine learning. These methods, she argues, encode segregation, eugenics, and identity politics through their default assumptions and conditions. Correlation, which grounds big data’s predictive potential, stems from twentieth-century eugenic attempts to “breed” a better future. Recommender systems foster angry clusters of sameness through homophily. Users are “trained” to become authentically predictable via a politics and technology of recognition. Machine learning and data analytics thus seek to disrupt the future by making disruption impossible. Chun, who has a background in systems design engineering as well as media studies and cultural theory, explains that although machine learning algorithms may not officially include race as a category, they embed whiteness as a default. Facial recognition technology, for example, relies on the faces of Hollywood celebrities and university undergraduates—groups not famous for their diversity. Homophily emerged as a concept to describe white U.S. resident attitudes to living in biracial yet segregated public housing. Predictive policing technology deploys models trained on studies of predominantly underserved neighborhoods. Trained on selected and often discriminatory or dirty data, these algorithms are only validated if they mirror this data. How can we release ourselves from the vice-like grip of discriminatory data? Chun calls for alternative algorithms, defaults, and interdisciplinary coalitions in order to desegregate networks and foster a more democratic big data.
Discriminating Data
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Author : Wendy Hui Kyong Chun
language : en
Publisher: MIT Press
Release Date : 2021-11-02
Discriminating Data written by Wendy Hui Kyong Chun and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-02 with Technology & Engineering categories.
How big data and machine learning encode discrimination and create agitated clusters of comforting rage. In Discriminating Data, Wendy Hui Kyong Chun reveals how polarization is a goal—not an error—within big data and machine learning. These methods, she argues, encode segregation, eugenics, and identity politics through their default assumptions and conditions. Correlation, which grounds big data’s predictive potential, stems from twentieth-century eugenic attempts to “breed” a better future. Recommender systems foster angry clusters of sameness through homophily. Users are “trained” to become authentically predictable via a politics and technology of recognition. Machine learning and data analytics thus seek to disrupt the future by making disruption impossible. Chun, who has a background in systems design engineering as well as media studies and cultural theory, explains that although machine learning algorithms may not officially include race as a category, they embed whiteness as a default. Facial recognition technology, for example, relies on the faces of Hollywood celebrities and university undergraduates—groups not famous for their diversity. Homophily emerged as a concept to describe white U.S. resident attitudes to living in biracial yet segregated public housing. Predictive policing technology deploys models trained on studies of predominantly underserved neighborhoods. Trained on selected and often discriminatory or dirty data, these algorithms are only validated if they mirror this data. How can we release ourselves from the vice-like grip of discriminatory data? Chun calls for alternative algorithms, defaults, and interdisciplinary coalitions in order to desegregate networks and foster a more democratic big data.
Summary Of Wendy Hui Kyong Chun S Discriminating Data
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Author : Milkyway Media
language : en
Publisher: Milkyway Media
Release Date : 2021-11-08
Summary Of Wendy Hui Kyong Chun S Discriminating Data written by Milkyway Media and has been published by Milkyway Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-08 with Study Aids categories.
Get the summary from Wendy Hui Kyong Chun's Discriminating Data #1 The Cambridge Analytica scandal showed how social media can be abused and manipulate elections. #2 Psychographics superseded demographics, geographics, and economics in terms of impact. It was determined that people’s personalities could be changed with rational, yet fear-based messages. #3 The claims made by Cambridge Analytica, and many other companies that use psychographic targeting, need to be taken with several grains of salt. Their efficacy has not yet been proven.
Algorithms Of Oppression
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Author : Safiya Umoja Noble
language : en
Publisher: NYU Press
Release Date : 2018-02-20
Algorithms Of Oppression written by Safiya Umoja Noble and has been published by NYU Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-20 with Computers categories.
Acknowledgments -- Introduction: the power of algorithms -- A society, searching -- Searching for Black girls -- Searching for people and communities -- Searching for protections from search engines -- The future of knowledge in the public -- The future of information culture -- Conclusion: algorithms of oppression -- Epilogue -- Notes -- Bibliography -- Index -- About the author
Measuring Racial Discrimination
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Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 2004-07-24
Measuring Racial Discrimination written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-07-24 with Social Science categories.
Many racial and ethnic groups in the United States, including blacks, Hispanics, Asians, American Indians, and others, have historically faced severe discriminationâ€"pervasive and open denial of civil, social, political, educational, and economic opportunities. Today, large differences among racial and ethnic groups continue to exist in employment, income and wealth, housing, education, criminal justice, health, and other areas. While many factors may contribute to such differences, their size and extent suggest that various forms of discriminatory treatment persist in U.S. society and serve to undercut the achievement of equal opportunity. Measuring Racial Discrimination considers the definition of race and racial discrimination, reviews the existing techniques used to measure racial discrimination, and identifies new tools and areas for future research. The book conducts a thorough evaluation of current methodologies for a wide range of circumstances in which racial discrimination may occur, and makes recommendations on how to better assess the presence and effects of discrimination.
Multivariate Data Reduction And Discrimination With Sas Software
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Author : Ravindra Khattree
language : en
Publisher: Wiley-SAS
Release Date : 2000-08-14
Multivariate Data Reduction And Discrimination With Sas Software written by Ravindra Khattree and has been published by Wiley-SAS this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-08-14 with Mathematics categories.
Easy to read and comprehensive, this book presents descriptive multivariate (DMV) statistical methods using real-world problems and data sets. It offers a unique approach to integrating statistical methods, various kinds of advanced data analyses, and applications of the popular SAS software aids. Emphasis is placed on the correct interpretation of output to draw meaningful conclusions in a variety of disciplines and industries.
Fundamentals Of Clinical Data Science
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Author : Pieter Kubben
language : en
Publisher: Springer
Release Date : 2018-12-21
Fundamentals Of Clinical Data Science written by Pieter Kubben and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-21 with Medical categories.
This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.
Discrimination And Privacy In The Information Society
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Author : Bart Custers
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-08-11
Discrimination And Privacy In The Information Society written by Bart Custers and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-11 with Technology & Engineering categories.
Vast amounts of data are nowadays collected, stored and processed, in an effort to assist in making a variety of administrative and governmental decisions. These innovative steps considerably improve the speed, effectiveness and quality of decisions. Analyses are increasingly performed by data mining and profiling technologies that statistically and automatically determine patterns and trends. However, when such practices lead to unwanted or unjustified selections, they may result in unacceptable forms of discrimination. Processing vast amounts of data may lead to situations in which data controllers know many of the characteristics, behaviors and whereabouts of people. In some cases, analysts might know more about individuals than these individuals know about themselves. Judging people by their digital identities sheds a different light on our views of privacy and data protection. This book discusses discrimination and privacy issues related to data mining and profiling practices. It provides technological and regulatory solutions, to problems which arise in these innovative contexts. The book explains that common measures for mitigating privacy and discrimination, such as access controls and anonymity, fail to properly resolve privacy and discrimination concerns. Therefore, new solutions, focusing on technology design, transparency and accountability are called for and set forth.
Reforming European Data Protection Law
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Author : Serge Gutwirth
language : en
Publisher: Springer
Release Date : 2014-11-17
Reforming European Data Protection Law written by Serge Gutwirth and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-17 with Law categories.
This book on privacy and data protection offers readers conceptual analysis as well as thoughtful discussion of issues, practices, and solutions. It features results of the seventh annual International Conference on Computers, Privacy, and Data Protection, CPDP 2014, held in Brussels January 2014. The book first examines profiling, a persistent core issue of data protection and privacy. It covers the emergence of profiling technologies, on-line behavioral tracking, and the impact of profiling on fundamental rights and values. Next, the book looks at preventing privacy risks and harms through impact assessments. It contains discussions on the tools and methodologies for impact assessments as well as case studies. The book then goes on to cover the purported trade-off between privacy and security, ways to support privacy and data protection, and the controversial right to be forgotten, which offers individuals a means to oppose the often persistent digital memory of the web. Written during the process of the fundamental revision of the current EU data protection law by the Data Protection Package proposed by the European Commission, this interdisciplinary book presents both daring and prospective approaches. It will serve as an insightful resource for readers with an interest in privacy and data protection.
Discriminating Risk
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Author : Guy Stuart
language : en
Publisher: Cornell University Press
Release Date : 2018-07-05
Discriminating Risk written by Guy Stuart and has been published by Cornell University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-05 with Political Science categories.
The U.S. home mortgage industry first formalized risk criteria in the 1920s and 1930s to determine which applicants should receive funds. Over the past eighty years, these formulae have become more sophisticated. Guy Stuart demonstrates that the very concepts on which lenders base their decisions reflect a set of social and political values about "who deserves what." Stuart examines the fine line between licit choice and illicit discrimination, arguing that lenders, while eradicating blatantly discriminatory practices, have ignored the racial and economic-class biases that remain encoded in their decision processes. He explains why African Americans and Latinos continue to be at a disadvantage in gaining access to loans: discrimination, he finds, results from the interaction between the way lenders make decisions and the way they shape the social structure of the mortgage and housing markets.Mortgage lenders, Stuart contends, are embedded in and shape a social context that can best be understood in terms of rules, networks, and the production of space. Stuart's history of lenders' risk criteria reveals that they were synthesized from rules of thumb, cultural norms, and untested theories. In addition, his interviews with real estate and lending professionals in the Chicago housing market show us how the criteria are implemented today. Drawing on census and Home Mortgage Disclosure Act data for quantitative support, Stuart concludes with concrete policy proposals that take into account the social structure in which lenders make decisions.