Discriminating systems. Gender, race, and AI.

Autor/inn/en	West, Sarah Myers; Whittaker, Meredith; Crawford, Kate
Institution	New York University / AI Now Institute
Titel	Discriminating systems. Gender, race, and AI. Gefälligkeitsübersetzung: Diskriminierende Systeme. Geschlecht, Rasse und künstliche Intelligenz.
Quelle	New York, NY (2019), 33 S. PDF als Volltext kostenfreie Datei Link als defekt meldenVerfügbarkeit
Sprache	englisch
Dokumenttyp	online; Monographie
Schlagwörter	Diversity Management; Stereotyp; Frau; Künstliche Intelligenz; Rasse; Diskriminierung; Gleichstellungspolitik; Sexuelle Belästigung; Beschäftigungsstruktur; Hochschullehrer; Informationswirtschaft; Informationswissenschaftler; Geschlechterverteilung; Geschlechtsspezifik; Schwarzer; Weißer; Informationswissenschaft; USA
Abstract	"The diversity problems of the AI industry and the issues of bias in AI systems tend to be considered separately. In this report we suggest that they are two sides of the same problem: issues of discrimination in the workforce and in system building are deeply related. Moreover, tackling the challenges of bias within technical systems requires addressing workforce diversity, and vice versa. Our research points to new ways of understanding the relationships between these complex problems, which can open up new pathways to redressing the current imbalances and harms.; Drawing on a thorough review of existing literature and current research working on issues of gender, race, class, and artificial intelligence, this pilot study examines the scale of AI's current diversity crisis and possible paths forward. It represents the first stage of a multi-year project examining the intersection of gender, race and power in AI." (Author's abstract, IAB-Doku).
Erfasst von	Institut für Arbeitsmarkt- und Berufsforschung, Nürnberg
Update	2020/1