Approximating Algorithms
From Discriminating Data to Talking With an Ai
Datos Bibliográficos
| ID | 4496705 |
|---|---|
| Autores | N Katherine Hayles (0000-0001-5922-1033, Duke University, autor de correspondencia) |
| Año | 2022 |
| Volumen | 61 |
| Número | 4 |
| Páginas | 152-165 |
| Fecha de publicación | 2022-12-01 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | History and Theory (JOURNAL) |
| Identificadores de la revista | ISSN: 0018-2656 • E-ISSN: 1468-2303 |
| Editorial | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/hith.12283 |
| OpenAlex | W4311216426 |
| Idioma | EN |
| Citas recibidas | 3 |
Wendy Hui Kyong Chun's Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition offers important tools to understand and, more importantly, transform the algorithms perpetuating and intensifying discrimination in North American societies. Unpacking her work's implications, this essay offers seven approximations-ranging from eliminating bias to rethinking the symbiotic relations between humans and computational media-as solutions to the problems she identifies. While some approximations reveal limitations in others, the clashes between them are due to the scope of the frameworks they employ. All are useful in the struggle to comprehend, in both small and large terms, the nature of the profound changes in the contemporary condition as computational media penetrate ever more deeply into the fabrics of our lives
Algorithm · Epistemology · Political science · Politics · Ranging · Scope (computer science) · Sociology · Unpacking · Artificial Intelligence · Computer Science · Ethics and Social Impacts of AI · Law · Philosophy
| Obras citantes distintas | 3 |
|---|---|
| Citas por año | 1 |
| Intervalo de citas | 2023 - 2025 (3) |
| Velocidad de citación | recent |
| Altamente citado | No |
| Tipos de cita | Neutras: 3 |