In this episode we examine the use of secret or black box algorithms for high-stake decisions, particularly in the criminal justice system. How do they factor in the decisions made every day by state and federal courts concerning bail, sentencing, and parole? Are black box algorithms fair and unbiased? Do they help counteract or support societal prejudices?  Is their use in criminal justice cases serving the public’s best interest? We discuss these issues and more with two experts on the topic: Cynthia Rudin, Professor of Computer Science, Electrical and Computer Engineering, Statistical Science, Mathematics, and Biostatistics & Bioinformatics and Director of the Interpretable Machine Learning Lab at Duke University and Brandon Garrett, Professor of Law and founder of the Wilson Center for Science and Justice at Duke University.