Machine learning algorithms are permeating our world. With applications in banking, investing, social media, advertising, and crime prevention, to name a few, these little black boxes are increasingly being used to inform and drive decisions about our lives and businesses. Machine Learning Risk Management is an often overlooked aspect of creating, deploying, and monitoring machine learning applications. Andrew will explain the dangers associated with an absence of controls during the machine learning process. He will then demonstrate how controls prevent modeling biases and suggest ways to develop and deploy machine learning applications with a control-centric, engineered approach.