The field of fair machine learning aims to ensure that decisions guided by algorithms are
equitable. Over the last decade, several formal, mathematical definitions of fairness have …

Police, prosecutors, judges, and other criminal justice actors increasingly use algorithmic
risk assessment to estimate the likelihood that a person will commit future crime. As many …

The law forbids discrimination. But the ambiguity of human decision-making often makes it
hard for the legal system to know whether anyone has discriminated. To understand how …

Over the past several years, a multitude of methods to measure the fairness of a machine
learning model have been proposed. However, despite the growing number of publications …

Supported by a large body of scholarship, it is increasingly orthodox practice for cities to
deploy urban greening interventions to address diverse socioenvironmental challenges …

Scholars and reformers have in recent years begun to imagine new and different
configurations for how the state can design policing institutions. These conversations have …

A Editora Contracorrente apresenta a segunda edição do aclamado livro" Pensando como
um Negro: Ensaio de Hermenêutica Jurídica". Trata-se uma obra bastante peculiar sobre …

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

Baltimore, Maryland. Buffalo, New York. Cleveland, Ohio. Chicago, Illinois. Cincinnati, Ohio.
Columbus, Ohio. Detroit, Michigan. East Haven, Connecticut. Ferguson, Missouri. Highland …

ABSTRACT A data revolution is transforming the workplace. Employers are increasingly
relying on algorithms to decide who gets interviewed, hired, or promoted. Although data …