Good for Whom?: Unsettling Research Practice
By L. Nathan, Michelle Kaczmarek, M. castor, Shannon K. Cheng, R. Mann. 2017
17 citations recorded by the source corpus.
Subfields: Management of Technology and Innovation, Sociology and Political Science, AI Ethics, Fairness & Society, Human-Computer Interaction, Social Sciences & Humanities
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Sociology and Political Science
In AI Ethics, Fairness & Society
In Human-Computer Interaction
In Social Sciences & Humanities
Citations in the corpus
- Re-imagining Algorithmic Fairness in India and Beyond (2021, background): “tise and experience necessary to identify what is of benefit to all [144].”