• Data Science for Criminal Justice: Can We Avoid Black Box Algorithms for High-Stake Decisions?

  • Jan 25 2022
  • Duración: 41 m
  • Podcast
Data Science for Criminal Justice: Can We Avoid Black Box Algorithms for High-Stake Decisions? Por arte de portada

Data Science for Criminal Justice: Can We Avoid Black Box Algorithms for High-Stake Decisions?

Escúchala gratis

Ver detalles del espectáculo

  • Resumen

  • 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.
    Más Menos
Política y Gobierno
Más Menos

Lo que los oyentes dicen sobre Data Science for Criminal Justice: Can We Avoid Black Box Algorithms for High-Stake Decisions?

Calificaciones medias de los clientes

Reseñas - Selecciona las pestañas a continuación para cambiar el origen de las reseñas.

Reseñas de Audible.com

Opiniones de Amazon
No hay comentarios disponibles