Discriminating Data Correlation, Neighborhoods, and the New Politics of Recognition
Afbeeldingen
Artikel vergelijken
Auteur:
Wendy Hui Kyong Chun
- Engels
- Hardcover
- 9780262046220
- 02 november 2021
- 312 pagina's
Samenvatting
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 goalnot an errorwithin 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 datas 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 undergraduatesgroups 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.
In Discriminating Data, Wendy Hui Kyong Chun reveals how polarization is a goalnot an errorwithin 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 datas 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 undergraduatesgroups 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.
Productspecificaties
Wij vonden geen specificaties voor jouw zoekopdracht '{SEARCH}'.
Inhoud
- Taal
- en
- Bindwijze
- Hardcover
- Oorspronkelijke releasedatum
- 02 november 2021
- Aantal pagina's
- 312
- Illustraties
- Met illustraties
Betrokkenen
- Hoofdauteur
- Wendy Hui Kyong Chun
- Hoofdillustrator
- Alex Barnett
- Tweede Illustrator
- Alex Barnett
- Hoofduitgeverij
- Mit Press Ltd
Overige kenmerken
- Studieboek
- Ja
- Verpakking breedte
- 152 mm
- Verpakking hoogte
- 229 mm
- Verpakking lengte
- 229 mm
- Verpakkingsgewicht
- 567 g
EAN
- EAN
- 9780262046220
Je vindt dit artikel in
- Categorieën
- Taal
- Engels
- Boek, ebook of luisterboek?
- Boek
- Beschikbaarheid
- Leverbaar
- Studieboek of algemeen
- Studieboeken
Kies gewenste uitvoering
Kies je bindwijze
(3)
Prijsinformatie en bestellen
De prijs van dit product is 29 euro en 95 cent.
Uiterlijk 3 mei in huis
Verkoop door bol
- Prijs inclusief verzendkosten, verstuurd door bol
- Ophalen bij een bol afhaalpunt mogelijk
- 30 dagen bedenktijd en gratis retourneren
- Dag en nacht klantenservice
Rapporteer dit artikel
Je wilt melding doen van illegale inhoud over dit artikel:
- Ik wil melding doen als klant
- Ik wil melding doen als autoriteit of trusted flagger
- Ik wil melding doen als partner
- Ik wil melding doen als merkhouder
Geen klant, autoriteit, trusted flagger, merkhouder of partner? Gebruik dan onderstaande link om melding te doen.