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Designing Tools for Semi-Automated Detection of Machine Learning Biases:
  An Interview Study

Designing Tools for Semi-Automated Detection of Machine Learning Biases: An Interview Study

13 March 2020
Po-Ming Law
Sana Malik
F. Du
Moumita Sinha
ArXivPDFHTML

Papers citing "Designing Tools for Semi-Automated Detection of Machine Learning Biases: An Interview Study"

3 / 3 papers shown
Title
Operationalizing Machine Learning: An Interview Study
Operationalizing Machine Learning: An Interview Study
Shreya Shankar
Rolando Garcia
J. M. Hellerstein
Aditya G. Parameswaran
71
51
0
16 Sep 2022
Balancing Biases and Preserving Privacy on Balanced Faces in the Wild
Balancing Biases and Preserving Privacy on Balanced Faces in the Wild
Joseph P. Robinson
Can Qin
Yann Henon
Samson Timoner
Y. Fu
32
25
0
16 Mar 2021
Improving fairness in machine learning systems: What do industry
  practitioners need?
Improving fairness in machine learning systems: What do industry practitioners need?
Kenneth Holstein
Jennifer Wortman Vaughan
Hal Daumé
Miroslav Dudík
Hanna M. Wallach
FaML
HAI
192
743
0
13 Dec 2018
1