What Makes an Algorithm Fair? | CDSS at UC Berkeley
The Age of Secrecy and Unfairness in Recidivism Prediction · Issue 2.1, Winter 2020
COMPAS Recidivism Racial Bias and How to Eliminate Biased Algorithms | by Jpuray | Medium
Chapter 10 Story COMPAS: recidivism reloaded | XAI Stories
How We Analyzed the COMPAS Recidivism Algorithm — ProPublica
Predictive Modeling Early
How We Analyzed the COMPAS Recidivism Algorithm — ProPublica
Chapter 10 Story COMPAS: recidivism reloaded | XAI Stories
Data and Discretion: Why We Should Exercise Caution Around Using the COMPAS Algorithm in Court | Stanford Rewired
The Age of Secrecy and Unfairness in Recidivism Prediction · Issue 2.1, Winter 2020
Algorithms are better than people in predicting recidivism, study says | Berkeley
The COMPAS Algorithm – It's not that black and white – The Little Data Scientist
Analysis of racial bias in Northpointe's COMPAS algorithm | Tulane University Digital Library
How We Analyzed the COMPAS Recidivism Algorithm — ProPublica
Grinnell DataSpace
Inside Track: The Loomis Case: The Use of Proprietary Algorithms at Sentencing:
Incident 40: COMPAS Algorithm Performs Poorly in Crime Recidivism Prediction
Incident 40: COMPAS Algorithm Performs Poorly in Crime Recidivism Prediction
How We Analyzed the COMPAS Recidivism Algorithm — ProPublica
Rachel Thomas on Twitter: "The Compas recidivism algorithm used in US courts has double the false positive rate (people rated high risk who do not reoffend) for Black defendants compared to white
Machine Learning/AI Bias. Deep learning algorithms are vastly… | by Divya Sikka | MLearning.ai | Medium
The Age of Secrecy and Unfairness in Recidivism Prediction · Issue 2.1, Winter 2020
A Popular Algorithm Is No Better at Predicting Crimes Than Random People - The Atlantic
Machine Bias — ProPublica
