Discriminating Data

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Release : 2021-11-02
Genre : Technology & Engineering
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Book Rating : 254/5 ( reviews)

Discriminating Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Discriminating Data write by Wendy Hui Kyong Chun. This book was released on 2021-11-02. Discriminating Data available in PDF, EPUB and Kindle. 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

Download Discriminating Data PDF Online Free

Author :
Release : 2021-11-02
Genre : Technology & Engineering
Kind :
Book Rating : 229/5 ( reviews)

Discriminating Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Discriminating Data write by Wendy Hui Kyong Chun. This book was released on 2021-11-02. Discriminating Data available in PDF, EPUB and Kindle. 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.

Algorithms of Oppression

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Release : 2018-02-20
Genre : Computers
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Book Rating : 245/5 ( reviews)

Algorithms of Oppression - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Algorithms of Oppression write by Safiya Umoja Noble. This book was released on 2018-02-20. Algorithms of Oppression available in PDF, EPUB and Kindle. 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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Release : 2004-07-24
Genre : Social Science
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Book Rating : 268/5 ( reviews)

Measuring Racial Discrimination - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Measuring Racial Discrimination write by National Research Council. This book was released on 2004-07-24. Measuring Racial Discrimination available in PDF, EPUB and Kindle. 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.

Pattern Discrimination

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Release : 2018-11-13
Genre : Social Science
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Book Rating : 277/5 ( reviews)

Pattern Discrimination - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Pattern Discrimination write by Clemens Apprich. This book was released on 2018-11-13. Pattern Discrimination available in PDF, EPUB and Kindle. How do “human” prejudices reemerge in algorithmic cultures allegedly devised to be blind to them? How do “human” prejudices reemerge in algorithmic cultures allegedly devised to be blind to them? To answer this question, this book investigates a fundamental axiom in computer science: pattern discrimination. By imposing identity on input data, in order to filter—that is, to discriminate—signals from noise, patterns become a highly political issue. Algorithmic identity politics reinstate old forms of social segregation, such as class, race, and gender, through defaults and paradigmatic assumptions about the homophilic nature of connection. Instead of providing a more “objective” basis of decision making, machine-learning algorithms deepen bias and further inscribe inequality into media. Yet pattern discrimination is an essential part of human—and nonhuman—cognition. Bringing together media thinkers and artists from the United States and Germany, this volume asks the urgent questions: How can we discriminate without being discriminatory? How can we filter information out of data without reinserting racist, sexist, and classist beliefs? How can we queer homophilic tendencies within digital cultures?