Evidence - Based Sentencing and the Scientific Rationalization of Discrimination Sonja

This paper critiques, on legal and empirical grounds, the growing trend of basing criminal sentences on actuarial recidivism risk prediction instruments that include demographic and socioeconomic variables. I argue that this practice violates the Equal Protection Clause and is bad policy: an explicit embrace of otherwise-condemned discrimination, sanitized by scientific language. To demonstrate that this practice should be subject to heightened constitutional scrutiny, I comprehensively review the relevant case law, much of which has been ignored by existing literature. To demonstrate that it cannot survive that scrutiny and is undesirable policy, I review the empirical evidence underlying the instruments. I show that they provide wildly imprecise individual risk predictions, that there is no compelling evidence that they outperform judges’ informal predictions, that less discriminatory alternatives would likely perform as well, and that the instruments do not even address the right question: the effect of a given sentencing decision on recidivism risk. Finally, I also present new, suggestive empirical evidence, based on a randomized experiment using fictional cases, that these instruments should not be expected merely to substitute actuarial predictions for less scientific risk assessments, but instead to increase the weight given to recidivism risk versus other sentencing considerations. * Professor of Law, University of Michigan. Thanks to Don Herzog, Ellen Katz, Richard Primus, and participants in Michigan Law’s Faculty Scholarship Brownbag Lunch for their comments, and to Grady Bridges, Matthew Lanahan, and Jarred Klorfein for research assistance. 66 STANFORD LAW REVIEW __ (FORTHCOMING 2014) ii INTRODUCTION ................................................................................................................. 1 I. Actuarial Risk Prediction and the Movement Toward Evidence-Based Sentencing ......... 5 II. The Disparate Treatment Concern ................................................................................ 12 A. Gender Classifications and the Problem with Statistical Discrimination ................................. 13 B. Wealth-Related Classifications in the Criminal Justice System .............................................. 17 C. The Social Harm of Demographic and Socioeconomic Sentencing Discrimination ................ 22 III. Assessing the Evidence for Evidence-Based Sentencing ............................................... 25 A. Precision, Group Averages, and Individual Predictions .......................................................... 26 B. Do the Instruments Outperform Clinical Prediction and Other Alternatives? ....................... 32 C. Do the Risk Prediction Instruments Address the Right Question? ......................................... 36 IV. Will Risk Prediction Instruments Really Change Sentencing Practice? ....................... 41 A. Does EBS Merely Provide Information? ................................................................................. 41 B. Does EBS Merely Replace One Form of Risk Prediction With Another? ............................... 43 CONCLUSION ................................................................................................................... 47 EVIDENCE-BASED SENTENCING AND THE SCIENTIFIC RATIONALIZATION OF DISCRIMINATION