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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: COLUM. SCI & TECH L. REV THE COLUMBIA SCIENCE & TECHNOLOGY LAW REVIEW VOL. XXI STLR.ORG SPRING 2020 ARTICLE BAIL OR JAIL? JUDICIAL VERSUS ALGORITHMIC DECISION- 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. 376 [Vol. XXI

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