Description
In this talk, we will first understand the emergence of bias in data and algorithmic decision making and present first steps towards developing a systematic framework to control biases in classical problems such as data summarization and personalization. This work leads to new algorithms that have the ability to alleviate bias and increase diversity while often simultaneously maintaining their the