Mr. Jones - Towards a proactive smart room orchestrator
Tathagata Chakraborti, Kartik Talamadupula, et al.
AAAI-FS 2017
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.
Tathagata Chakraborti, Kartik Talamadupula, et al.
AAAI-FS 2017
Priya Nagpurkar, Michael Hind, et al.
CGO 2006
Ameneh Shamekhi, Q. Vera Liao, et al.
CHI 2018
Dries Buytaert, Andy Georges, et al.
OOPSLA 2007