Racial Equity in Algorithmic Criminal Justice

Posted: 24 Mar 2018  

Aziz Z. Huq

University of Chicago - Law School

Date Written: March 20, 2018

Abstract

Algorithmic tools for predicting violence and criminality are increasingly used in policing, bail, and sentencing contexts. Although some attention has been given to their procedural due process implications, how these instruments interact with the enduring and complex racial legacies of the criminal justice system is presently not well understood. This Article analyzes the questions of racial equity raised by these new predictive instruments using two lenses: constitutional doctrine and emerging technical standards of “algorithmic fairness.” I demonstrate that constitutional doctrine is poorly adapted to addressing the range of racial issues that potentially arise with algorithmic criminal justice. Instead, I demonstrate that the difficult questions of racial equity in this domain are best framed and evaluated though certain, but not all, emerging technical standards of algorithmic fairness.

Keywords: Machine learning; criminal justice; racial equality

Suggested Citation

Huq, Aziz Z., Racial Equity in Algorithmic Criminal Justice (March 20, 2018). Duke Law Journal, Vol. 68; U of Chicago, Public Law Working Paper No. 663. Available at SSRN: https://ssrn.com/abstract=3144831

Aziz Z. Huq (Contact Author)

University of Chicago - Law School ( email )

1111 E. 60th St.
Chicago, IL 60637
United States

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