Loop distribution with multiple exits
Bor-Ming Hsieh, Michael Hind, et al.
ACM/IEEE SC 1992
Today, machine-learning software is used to help make decisions that affect people's lives. Some people believe that the application of such software results in fairer decisions because, unlike humans, machine-learning software generates models that are not biased. Think again. Machine-learning software is also biased, sometimes in similar ways to humans, often in different ways. While fair model- assisted decision making involves more than the application of unbiased models-consideration of application context, specifics of the decisions being made, resolution of conflicting stakeholder viewpoints, and so forth-mitigating bias from machine-learning software is important and possible but difficult and too often ignored.
Bor-Ming Hsieh, Michael Hind, et al.
ACM/IEEE SC 1992
Kuntal Dey, Ritvik Shrivastava, et al.
ICDMW 2017
Ravi Kiran Raman, Kush R. Varshney, et al.
ICASSP 2019
Abhijit Mishra, Srikanth Tamilselvam, et al.
AAAI 2018