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21 Colum. Sci. & Tech. L. Rev. 376 (2019-2020)
Bail Or Jail? Judicial versus Algorithmic Decision-Making in the Pretrial System

handle is hein.journals/cstlr21 and id is 386 raw text is: 



      SCIENCE &



VOL.  XXI                    STLR.ORG                    SPRING  2020


                 MAKING   IN THE  PRETRIAL   SYSTEM

                        Doaa   Abu  Elyounes*

        To date, there are approximately sixy risk assessment tools deployed in
the criminal justice system. These tools aim to differentiate between low-,
medium-, and high-risk defendants and to increase the likelihood that only those
who pose a risk to public safety or who are likely to flee are detained. Proponents
of actuarial tools claim that these tools are meant to eliminate human biases and
to rationalize the decision-making process by summarizing  all relevant
information in a more efficient way than can the human brain. Opponents ofsuch
toolsfear that in the name of science, actuarial tools reinforce human biases, harm
defendants' nghts, and increase racial disparities in the system. he gap between
the two camps has widened in the last few years. Policymakers are torn between
the promise of technology to contribute to a more just system and a growing
movement that callsfor the abolishment of the use of actuarial risk assessment
tools in general and the use of machine learning-based tools in particular.
        This paper examines the role that technology plays in this debate and
examines  whether deploying artificial intelligence (AP') in existing risk
assessment tools realizes the fears emphasized by opponents of automation or
improves our criminal justice system. It focuses on the pretrial stage and examines
in depth the seven most commonly used tools. Five of these tools are based on
traditional regression analysis, and two have a machine-learning component. This

    *   Author   Harvard Law School; and Berkman Klein Center for Internet
and Society at Harvard University (email: dabuelyounes@sjd.law.harvard.edu). I
would like to express my gratitude to my supervisor, Professor Yochai Benkler,
and to Professor Carol Steiker and Professor Niva Elkin-Koren for their extremely
helpful guidance throughout the writing process. Earlier drafts of this work were
presented at the AI & Law Conference at Seton Hall Law School, at the Cyber
Challenges to Human Rights Conference in the University of Haifa, and at an AI
Colloquium at the Berkman Klein Center; I am grateful for the helpful comments
provided by the participants at these events.


[Vol. XXI

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