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29 Kan. J.L. & Pub. Pol'y 329 (2019-2020)
When They Hear Us: Race, Algorithms and the Practice of Criminal Law

handle is hein.journals/kjpp29 and id is 352 raw text is: 












    WHEN THEY HEAR US: RACE, ALGORITHMS AND THE
                   PRACTICE OF CRIMINAL LAW


                             By: Ngozi Okidegbe*

                             I. INTRODUCTION

     Good morning. Thank you for that wonderful introduction. I would like to
thank the editors of the Kansas Journal of Law and Public Policy for inviting
me here today to speak at this timely symposium about work and the way in
which new technologies are affecting work. I think that this symposium has
situated itself in a broader conversation about the ways in which new
technologies are shaping and reorienting social and legal processes and
structures.' It is my pleasure to discuss this phenomenon as it relates to race,
algorithms, and the practice of criminal law.
     Algorithms are transforming the daily practice of criminal law. These
algorithms use statistical methods and big data to predict outcomes at different
levels of the criminal justice system. Police are using algorithms to predict
which individuals are at high risk of committing or being the victim of
violence.2 Pre-trial algorithms, which are designed to predict the statistical risk
of a defendant's risk of flight or pre-trial crime, are being relied upon by bail
judges to inform their decision to release or to detain a defendant before trial.3
Sentencing algorithms, that purport to predict an offender's risk of recidivism,

* Assistant Professor of Law, Benjamin N. Cardozo School of Law. My thanks to the student
editors of the Kansas Journal of Law & Public Policy for their thoughtful editing. This Article is
based on my keynote address, When They Hear Us: Race, Algorithms and The Practice of
Criminal Law, at the 2020 Kansas Journal of Law & Public Policy Symposium on Friday,
February 28, 2020 and reflects the current state of developments as of that date. The author's
position on communal inclusion in algorithmic governance has evolved since this speech was
given. For a fuller account, see Ngozi Okidegbe, The Democratizing Potential of Algorithms, 53
CONN. L. REv. (forthcoming 2021) (on file with author).
1 See generally CATHY O'NEIL, WEAPONS OF MATH DESTRUCTION: How BIG DATA INCREASES
INEQUALITY AND THREATENS DEMOCRACY (2016); VIRGINIA EUBANKS, AUTOMATING
INEQUALITY: How HIGH-TECH TOOLS PROFILE, POLICE, AND PUNISH THE POOR (2018).
2 Andrew Guthrie Ferguson, Illuminating Black Data Policing, 15 OHIO ST. J. CRIM. L. 503, 505
06 (2018).
' Sandra G. Mayson, Dangerous Defendants, 127 YALE L.J. 490, 508 10 (2018) [hereinafter
Mayson, Dangerous Defendants].

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