Artificial intelligence (AI) and algorithmic decision making are having a profound impact on
our daily lives. These systems are vastly used in different high-stakes applications like …

A recent wave of research has attempted to define fairness quantitatively. In particular, this
work has explored what fairness might mean in the context of decisions based on the …

Black box machine learning models are currently being used for high-stakes decision
making throughout society, causing problems in healthcare, criminal justice and other …

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 …

Algorithms for predicting recidivism are commonly used to assess a criminal defendant's
likelihood of committing a crime. These predictions are used in pretrial, parole, and …

Adolescenceâ€" beginning with the onset of puberty and ending in the mid-20sâ€" is a
critical period of development during which key areas of the brain mature and develop …

The machine learning community has become increasingly concerned with the potential for
bias and discrimination in predictive models. This has motivated a growing line of work on …

Algorithmic decision making is employed in an increasing number of real-world applications
to aid human decision making. While it has shown considerable promise in terms of …

While algorithm audits are growing rapidly in commonality and public importance, relatively
little scholarly work has gone toward synthesizing prior work and strategizing future research …