Chun Alex (100 results)

paperback. Condition: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority.

Paperback. Condition: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority.

Paperback. Condition: New. Paperback. Publisher overstock, may contain remainder mark on edge. Barnett, Alex (illustrator).

Hard Cover. Condition: vg+. Dust Jacket Condition: vg-. 1st ptg. 282 pages; yellow dust jacket has some rippling. Alex Camlin, dj il (illustrator). Hardcover (dj).

paperback. Condition: New. Barnett, Alex (illustrator).

Condition: New. Barnett, Alex (illustrator).

Paperback. Condition: New. 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. Barnett, Alex (illustrator).…

Paperback. Condition: new. Paperback. How big data and machine learning encode discrimination and create agitated clusters of comforting rage.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. "Chun investigates the centrality of race, gender, class, and sexuality to "Big Data" and network analytics"-- Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Barnett, Alex (illustrator).…

Condition: Good. Good condition. No Dust Jacket A copy that has been read but remains intact. May contain markings such as bookplates, stamps, limited notes and highlighting, or a few light stains.

Paperback. Condition: New. Barnett, Alex (illustrator).

Condition: As New. Unread book in perfect condition. Barnett, Alex (illustrator).

Condition: New. Barnett, Alex (illustrator).

paperback. Condition: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority.

DVD. Condition: New. Still new in plastic.

hardcover. Condition: Good. No dust jacket. Very minor wear.No marks in text.

Hardback. Condition: Very Good. 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. Barnett, Alex (illustrator). …

Condition: New. Barnett, Alex (illustrator).

hardcover. Condition: Very Good.

Hardback. Condition: Very Good. 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. Barnett, Alex (illustrator). …

Condition: very_good. This book is in Very good condition. There may be a few flaws like shelf wear and some light wear.

Condition: New. 2024. Paperback. . . . . . Barnett, Alex (illustrator).

Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Barnett, Alex (illustrator).

Condition: New. 2024. Paperback. . . . . . Books ship from the US and Ireland. Barnett, Alex (illustrator).

Condition: New. Barnett, Alex (illustrator).

hardcover. Condition: Very Good. With wrap-around flap very good.

Hardcover. Condition: Very Good. No Jacket. Obi is present. Slight bump to head of spine cover.

Paperback. Condition: Fine. COMIC ART ISSUE NUMBER FIVE (Insert by Rick Prol) with textx by Prol, Rcik; Philip Nel; Sally, Zak; Hignite, M. Todd; Chun, Alex; Posenkranz, Patrick. Stories about Crockett Johnson, Kim Deitch, Art Spiegelman, Don Flowers, Rand Holmes, Johnny Craig. Cover by Art Spiegelman. 80 pages, 11" x 8 1/2". High quality color and black and white reproductions. Prol's insert is framable. Fine condition.…

hardcover. Condition: Good. Good condition hardback. Pages are clean and unmarked. Minor edgewear and corner bumping. Light discoloration on cover edges and on textblock edges. Tulsa's largest used bookstore. Located on South Mingo Road since 1991. No-hassle return policy if not completely satisfied.…

Hardcover. Condition: Very Good. Dust Jacket Condition: Very Good. Book has light wear to most edges, but slightly crushed at top of spine. Otherwise, attractive copy with clean, unmarked pages and solid binding. Half-jacket has 1" closed tear at spine. Otherwise, attractive and clean. Pictures available upon request.…

Paperback. Condition: Brand New. 327 pages. 8.50x5.50x1.00 inches. In Stock. Barnett, Alex (illustrator).