2018
Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer
NeurIPS 2018poster
In many machine learning applications, there are multiple decision-makers involved, both automated and human. The interaction between these agents often goes unaddressed in algorithmic development. In this work, we explore a simple version of this interaction with a two-stage framework containing an…