Seminar Series with Sendhil Mullainathan: Automated Discovery of Human Biases скачать в хорошем качестве

Seminar Series with Sendhil Mullainathan: Automated Discovery of Human Biases

On November 15, 2021, Professor Sendhil Mullainathan of The University of Chicago Booth School of Business joined S-DEL Director Erik Brynjolfsson to discuss the automated discovery of human biases. Abstract Science begins with something curiously non-scientific. Scientists meticulously test hypotheses that themselves come from a very messy place: a mix of creativity, intuition, observation and chance. We argue machine learning can play a more rigorous role here. We illustrate this in a problem that is of great conceptual and practical interest: how do judges decide whom to jail? A deep learning algorithm trained on past data discovers a striking behavioral error: a defendant's face alone accounts for 30% of the explainable variation in whom judges choose to jail. This finding is not explained by race, skin color, demographics or other known factors. To make the discovery usable, we develop a procedure that allows the algorithm to communicate what it is seeing in the face. This leads us to identify facial features, previously not considered, that bias the way judges treat defendants.