NCDS DataBytes | AI Ethics Through the Lens of Causality : A Theory of Fairness

To understand fairness, one must unify central ideas from the social sciences and humanities to mathematics and computer science. Join Christopher Lam, CEO of Epistamai, as he shows how to model a principal cause of algorithmic bias and directly map it to the two fundamental laws of causal inference. Additionally, he will show how to bridge the field of causal inference to machine learning, providing us with a novel way to visualize the different ways that a supervised machine learning model can discriminate. These causal models may help policymakers on both sides of the aisle to modernize AI regulations so that they are aligned to society’s values. Learn more on their website.