Aziz Huq Reviews "Just Algorithms" by Vanderbilt Law Prof. Christopher Slobogin
Just Algorithms: Using Science To Reduce Incarceration And Inform A Jurisprudence Of Risk
Even if the Black Lives Matter (BLM) movement has not achieved its “defund” ambition for municipal policing—and the evidence is decidedly mixed—it has plainly struck criminal justice scholarship like a bolt of lightning (Marcellin & Doyle, 2020). A scholarly work that brackets or marginalizes the distinctive scale and racialized character of American policing and the associated carceral state risks being taken less than seriously or ignored, even if it offers a contribution to a different, important conversation within the world of criminal justice.
As evidence of this re-orienting change, consider the most recent book by the eminent criminal justice scholar Christopher Slobogin. Professor Slobogin has been teaching and writing (now at Vanderbilt Law School) about diverse problems thrown up administrating the criminal justice, mental health, and juvenile justice systems for more than two and a half decades. He is author of six monographs, including deservedly respected volumes about risk, preventive detention, and privacy, as well as dozens of law review articles across many leading journals. At its core, his new book Just Algorithms is a continuation of themes addressed at length in much of that earlier work. But Slobogin frames the decision to use risk assessment instruments (RAIs) as a superior policy response to the “plague of mass incarceration” (p. 1). Consciously writing in light of BLM protests, he perceives a “consensus” among policymakers over the need to reduce the number of incarcerated persons, and proposes RAIs as a means to that end (p. 24). His contribution hence asks to be evaluated in relation to that larger social project, rather than more narrowly as an exploration of the design and implementation of RAIs.
I don’t think that Just Algorithms will persuade the many racial justice advocates and scholars who are skeptical of RAIs, and who would prefer to move directly toward decarceration (The Use of Pretrial “Risk Assessment” Instruments, n.d.). Indeed, for reasons I’ll get to below, I am not sure that Slobogin has persuaded himself when he postulates that RAIs can be an effective response to the political problem of racialized mass incarceration. More modestly, however, Slobogin’s book succeeds as a careful and illuminating discussion of the key technical questions presented by RAIs in current use today. In his best moments, Slobogin adumbrates crisply and lucidly the key distinctions between different forms of RAIs, isolates the most important accuracy-related parameters, and provides a powerful argument against allowing human overrides of machine judgment (which almost always generate higher error rates) (Huq, 2020).
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