Artificial intelligence (AI) is producing highly beneficial impacts in many domains, from
transport to healthcare, from energy distribution to marketing, but it also raises concerns …

Objectives: Discussions of fairness in criminal justice risk assessments typically lack
conceptual precision. Rhetoric too often substitutes for careful analysis. In this article, we …

Abstract Mixup~\cite {zhang2017mixup} is a recently proposed method for training deep
neural networks where additional samples are generated during training by convexly …

Can machine learning improve human decision making? Bail decisions provide a good test
case. Millions of times each year, judges make jail-or-release decisions that hinge on a …

Machine learning models in safety-critical settings like healthcare are often “blackboxes”:
they contain a large number of parameters which are not transparent to users. Post-hoc …

In this Article, I explore the impending conflict between the protection of civil rights and
artificial intelligence (AI). While both areas of law have amassed rich and well-developed …

At the forefront of the evidence-based criminal justice movement are algorithmic risk
assessment tools. 3 Risk assessment tools are designed to predict the likelihood that …

Algorithmic tools for predicting violence and criminality are increasingly deployed in
policing, bail, and sentencing. Scholarly attention to date has focused on these tools' …

Algorithms (in some form) are already widely used in the criminal justice system. We draw
lessons from this experience for what is to come for the rest of society as machine learning …

Artificial Intelligence (AI) education is an increasingly popular topic area for K-12 teachers.
However, little research has investigated how AI curriculum and tools can be designed to be …