Challenging Racist Predictive Policing Algorithms Under the Equal Protection Clause
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Improving Recidivism As a Performance Measure Ryan King Brian Elderbroom Washington State Offender Accountability Act of 1999
Improving Recidivism as a Performance Measure Ryan King Brian Elderbroom Washington State Offender Accountability Act of 1999 Goal: “reduce the risk of reoffending by offenders in the community” Legislation calls for Department of Corrections to: • Classify supervised individuals based on risk of reoffending and severity of prior criminal offending • Shift resources toward higher-risk persons Washington Recidivism Rates Source: Washington State Institute for Public Policy Establishing Metrics for Success and Assessing Results Why measure correctional performance? • Understand the outcomes of funding and policy decisions • Assess the effectiveness of justice agencies at reducing reoffending • Provide the best return on taxpayer investments Most Common Correctional Performance Measure: Recidivism The Good: • Correctional interventions (prison, community supervision) are supposed to reduce reoffending, so recidivism is a natural metric for success The Bad: • Frequently a single-indicator, which doesn’t allow for policy-relevant comparisons across groups • Irregularly collected • Presented absent context Four Steps to Make Recidivism a Meaningful Performance Measure Define Collect Analyze Disseminate Definition Use Multiple Measures of Success Desistance Severity Time to failure Behavior Change Time to Failure (Delaware) Percent Rearrested 2008 2009 2010 80 70 60 50 40 30 20 10 0 6 12 18 24 36 Months from prison release Collection Develop Protocols to Ensure Data Are Consistent, Accurate, and Timely Assign unique identifiers Develop long-term records Collect contextual information Update change in status Photo: Flickr/Kevin Dl Breaking Recidivism Down by Policy- Relevant Factors (Colorado) 3-year return to prison rates for 2010 release cohort Analysis Account for Underlying Composition of the Prison Population Photo: Flickr/Thomas Hawk Photo: Flickr/Thomas Hawk Remember that Washington Story from Earlier . -
Prison Abolition and Grounded Justice
Georgetown University Law Center Scholarship @ GEORGETOWN LAW 2015 Prison Abolition and Grounded Justice Allegra M. McLeod Georgetown University Law Center, [email protected] This paper can be downloaded free of charge from: https://scholarship.law.georgetown.edu/facpub/1490 http://ssrn.com/abstract=2625217 62 UCLA L. Rev. 1156-1239 (2015) This open-access article is brought to you by the Georgetown Law Library. Posted with permission of the author. Follow this and additional works at: https://scholarship.law.georgetown.edu/facpub Part of the Criminal Law Commons, Criminal Procedure Commons, Criminology Commons, and the Social Control, Law, Crime, and Deviance Commons Prison Abolition and Grounded Justice Allegra M. McLeod EVIEW R ABSTRACT This Article introduces to legal scholarship the first sustained discussion of prison LA LAW LA LAW C abolition and what I will call a “prison abolitionist ethic.” Prisons and punitive policing U produce tremendous brutality, violence, racial stratification, ideological rigidity, despair, and waste. Meanwhile, incarceration and prison-backed policing neither redress nor repair the very sorts of harms they are supposed to address—interpersonal violence, addiction, mental illness, and sexual abuse, among others. Yet despite persistent and increasing recognition of the deep problems that attend U.S. incarceration and prison- backed policing, criminal law scholarship has largely failed to consider how the goals of criminal law—principally deterrence, incapacitation, rehabilitation, and retributive justice—might be pursued by means entirely apart from criminal law enforcement. Abandoning prison-backed punishment and punitive policing remains generally unfathomable. This Article argues that the general reluctance to engage seriously an abolitionist framework represents a failure of moral, legal, and political imagination. -
Evaluation of the Shreveport Predictive Policing Experiment
Safety and Justice Program CHILDREN AND FAMILIES The RAND Corporation is a nonprofit institution that EDUCATION AND THE ARTS helps improve policy and decisionmaking through ENERGY AND ENVIRONMENT research and analysis. HEALTH AND HEALTH CARE This electronic document was made available from INFRASTRUCTURE AND www.rand.org as a public service of the RAND TRANSPORTATION Corporation. INTERNATIONAL AFFAIRS LAW AND BUSINESS NATIONAL SECURITY Skip all front matter: Jump to Page 16 POPULATION AND AGING PUBLIC SAFETY SCIENCE AND TECHNOLOGY TERRORISM AND HOMELAND SECURITY Support RAND Purchase this document Browse Reports & Bookstore Make a charitable contribution For More Information Visit RAND at www.rand.org Explore the RAND Safety and Justice Program View document details Limited Electronic Distribution Rights This document and trademark(s) contained herein are protected by law as indicated in a notice appearing later in this work. This electronic representation of RAND intellectual property is provided for non-commercial use only. Unauthorized posting of RAND electronic documents to a non-RAND website is prohibited. RAND electronic documents are protected under copyright law. Permission is required from RAND to reproduce, or reuse in another form, any of our research documents for commercial use. For information on reprint and linking permissions, please see RAND Permissions. This report is part of the RAND Corporation research report series. RAND reports present research findings and objective analysis that ad- dress the challenges facing the public and private sectors. All RAND reports undergo rigorous peer review to ensure high standards for re- search quality and objectivity. Evaluation of the Shreveport Predictive Policing Experiment Priscillia Hunt, Jessica Saunders, John S. -
Recidivism Among Federal Violent Offenders
Recidivism Among Federal Violent Offenders UNITED STATES SENTENCING COMMISSION United States Sentencing Commission One Columbus Circle, N.E. Washington, DC 20002 www.ussc.gov William H. Pryor Jr. Acting Chair Rachel E. Barkow Commissioner Charles R. Breyer Commissioner Danny C. Reeves Commissioner Patricia K. Cushwa Ex Officio David Rybicki Ex Officio Kenneth P. Cohen Staff Director Glenn R. Schmitt Director Office of Research and Data January 2019 Kim Steven Hunt, Ph.D., Senior Research Associate Matthew J. Iaconetti, J.D., M.A., Assistant General Counsel Kevin T. Maass, M.A., Research Associate TABLE OF CONTENTS Chapter One Chapter Two Chapter Three Chapter Four VIOLENT AND VIOLENT VIOLENT EXECUTIVE SUMMARY NON-VIOLENT OFFENDERS INSTANT OFFENDERS PRIOR OFFENDERS Introduction.........................................2 Offender and Offense Offender and Offense Offender and Offense Characteristics....................................8 Characteristics..................................18 Characteristics..................................30 Key Findings........................................3 Recidivism Findings...........................11 Recidivism Findings...........................21 Recidivism Findings...........................33 Measures of Recidivism and Methodology......................................4 Robbery Offenders............................27 i Chapter One Chapter Two Chapter Three Chapter Four Chapter Five APPENDICES VIOLENT AND VIOLENT VIOLENT EXECUTIVE SUMMARY NON-VIOLENT OFFENDERS INSTANT OFFENDERS PRIOR OFFENDERS CONCLUSION -
Introductory Handbook on the Prevention of Recidivism and the Social Reintegration of Offenders
Introductory Handbook on The Prevention of Recidivism and the Social Reintegration of Offenders CRIMINAL JUSTICE HANDBOOK SERIES Cover photo: © Rafael Olivares, Dirección General de Centros Penales de El Salvador. UNITED NATIONS OFFICE ON DRUGS AND CRIME Vienna Introductory Handbook on the Prevention of Recidivism and the Social Reintegration of Offenders CRIMINAL JUSTICE HANDBOOK SERIES UNITED NATIONS Vienna, 2018 © United Nations, December 2018. All rights reserved. The designations employed and the presentation of material in this publication do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area, or of its authorities, or concerning the delimitation of its frontiers or boundaries. Publishing production: English, Publishing and Library Section, United Nations Office at Vienna. Preface The first version of the Introductory Handbook on the Prevention of Recidivism and the Social Reintegration of Offenders, published in 2012, was prepared for the United Nations Office on Drugs and Crime (UNODC) by Vivienne Chin, Associate of the International Centre for Criminal Law Reform and Criminal Justice Policy, Canada, and Yvon Dandurand, crimi- nologist at the University of the Fraser Valley, Canada. The initial draft of the first version of the Handbook was reviewed and discussed during an expert group meeting held in Vienna on 16 and 17 November 2011.Valuable suggestions and contributions were made by the following experts at that meeting: Charles Robert Allen, Ibrahim Hasan Almarooqi, Sultan Mohamed Alniyadi, Tomris Atabay, Karin Bruckmüller, Elias Carranza, Elinor Wanyama Chemonges, Kimmett Edgar, Aida Escobar, Angela Evans, José Filho, Isabel Hight, Andrea King-Wessels, Rita Susana Maxera, Marina Menezes, Hugo Morales, Omar Nashabe, Michael Platzer, Roberto Santana, Guy Schmit, Victoria Sergeyeva, Zhang Xiaohua and Zhao Linna. -
Predictive POLICING the Role of Crime Forecasting in Law Enforcement Operations
Safety and Justice Program CHILDREN AND FAMILIES The RAND Corporation is a nonprofit institution that EDUCATION AND THE ARTS helps improve policy and decisionmaking through ENERGY AND ENVIRONMENT research and analysis. HEALTH AND HEALTH CARE This electronic document was made available from INFRASTRUCTURE AND www.rand.org as a public service of the RAND TRANSPORTATION Corporation. INTERNATIONAL AFFAIRS LAW AND BUSINESS NATIONAL SECURITY Skip all front matter: Jump to Page 16 POPULATION AND AGING PUBLIC SAFETY SCIENCE AND TECHNOLOGY TERRORISM AND HOMELAND SECURITY Support RAND Purchase this document Browse Reports & Bookstore Make a charitable contribution For More Information Visit RAND at www.rand.org Explore the RAND Safety and Justice Program View document details Limited Electronic Distribution Rights This document and trademark(s) contained herein are protected by law as indicated in a notice appearing later in this work. This electronic representation of RAND intellectual property is provided for non-commercial use only. Unauthorized posting of RAND electronic documents to a non-RAND website is prohibited. RAND electronic documents are protected under copyright law. Permission is required from RAND to reproduce, or reuse in another form, any of our research documents for commercial use. For information on reprint and linking permissions, please see RAND Permissions. This report is part of the RAND Corporation research report series. RAND reports present research findings and objective analysis that ad- dress the challenges facing the public and private sectors. All RAND reports undergo rigorous peer review to ensure high standards for re- search quality and objectivity. Safety and Justice Program PREDICTIVE POLICING The Role of Crime Forecasting in Law Enforcement Operations Walter L. -
They Tried to Make Me Go to Rehab: a Study of Rehabilitation in United States Corrections Kayla J
University of Rhode Island DigitalCommons@URI Senior Honors Projects Honors Program at the University of Rhode Island 2015 They Tried to Make Me Go To Rehab: A Study of Rehabilitation in United States Corrections Kayla J. Toole University of Rhode Island, [email protected] Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 License. Follow this and additional works at: http://digitalcommons.uri.edu/srhonorsprog Part of the Cognitive Psychology Commons, Criminology Commons, Family, Life Course, and Society Commons, and the Social Control, Law, Crime, and Deviance Commons Recommended Citation Toole, Kayla J., "They rT ied to Make Me Go To Rehab: A Study of Rehabilitation in United States Corrections" (2015). Senior Honors Projects. Paper 387. http://digitalcommons.uri.edu/srhonorsprog/387http://digitalcommons.uri.edu/srhonorsprog/387 This Article is brought to you for free and open access by the Honors Program at the University of Rhode Island at DigitalCommons@URI. It has been accepted for inclusion in Senior Honors Projects by an authorized administrator of DigitalCommons@URI. For more information, please contact [email protected]. Running Head: REHABILITATION IN CORRECTIONS 1 They Tried to Make Me Go To Rehab: A Study on Rehabilitation in United States Corrections Kayla J. Toole University of Rhode Island REHABILITATION IN CORRECTIONS 2 Abstract Rehabilitation has been a staple of the prison system in the United States since the 1700s. The idea that a criminal could be resocialized into a functioning individual in society has been the basis of the prison systems since they first began. Rehabilitation is always evolving in the criminal justice system and being improved to have more impact on recidivism rates. -
How Will AI Shape the Future of Law?
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Helsingin yliopiston digitaalinen arkisto How Will AI Shape the Future of Law? EDITED BY RIIKKA KOULU & LAURA KONTIAINEN 2019 Acknowledgements The editors and the University of Helsinki Legal Tech Lab would like to thank the authors and interviewees for the time and effort they put into their papers. We would also like to thank the Faculty of Law at University of Helsinki and particularly the continuous kind support of Professor Kimmo Nuotio, the former dean of the faculty and the Lab’s unofficial godfather, for facilitating the Lab’s development and for helping us make the second Legal Tech Conference happen. In addition, we would like to express our gratitude to the conference sponsors, Finnish Bar Association, the Association of Finnish Lawyers, Edita Publishing, Attorneys at Law Fondia and Attorneys at Law Roschier as well as the Legal Design Summit community for their support. It takes a village to raise a conference. Therefore, we would like to thank everyone whose time and commitment has turned the conference and this publication from an idea into reality. Thank you to the attendees, speakers, volunteers and Legal Tech Lab crew members. RIIKKA KOULU & LAURA KONTIAINEN Legal Tech Lab, University of Helsinki 2019 University of Helsinki Legal Tech Lab publications © Authors and Legal Tech Lab ISBN 978-951-51-5476-7 (print) ISBN 978-951-51-5477-4 (PDF) Print Veiters Helsinki 2019 Contents Foreword 009 KIMMO NUOTIO I Digital Transformation of -
Establishing Discriminatory Purpose in Algorithmic Risk Assessment
NOTES BEYOND INTENT: ESTABLISHING DISCRIMINATORY PURPOSE IN ALGORITHMIC RISK ASSESSMENT Equal protection doctrine is bound up in conceptions of intent. Unintended harms from well-meaning persons are, quite simply, nonac- tionable.1 This basic predicate has erected a high bar for plaintiffs ad- vancing equal protection challenges in the criminal justice system. Notably, race-based challenges on equal protection grounds, which sub- ject the state to strict scrutiny review, are nonetheless stymied by the complexities of establishing discriminatory purpose. What’s more, the inability of courts and scholars to coalesce on a specific notion of the term has resulted in gravely inconsistent applications of the doctrine.2 States’ increasing use of algorithmic systems raises longstanding con- cerns regarding prediction in our criminal justice system — how to cat- egorize the dangerousness of an individual, the extent to which past behavior is relevant to future conduct, and the effects of racial dispari- ties.3 Integration of algorithmic systems has been defined by ambiva- lence: while they are touted for their removal of human discretion,4 they also readily promote and amplify inequalities — for example, through their consideration of protected characteristics and their interaction with existing systems tainted by legacies of inequality.5 Furthermore, algo- rithms, especially those incorporating artificial intelligence (AI), may operate in ways that are opaque, unpredictable, or not well understood. ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 See Washington v. Davis, 426 U.S. 229, 239–40 (1976). 2 See Aziz Z. Huq, What Is Discriminatory Intent?, 103 CORNELL L. REV. 1211, 1240–63 (2018) (presenting five definitions from the literature). 3 See Sonia K. -
Recidivism Among Female Prisoners: Secondary Analysis of the 1994 BJS Recidivism Data Set
The author(s) shown below used Federal funds provided by the U.S. Department of Justice and prepared the following final report: Document Title: Recidivism Among Female Prisoners: Secondary Analysis of the 1994 BJS Recidivism Data Set Author(s): Elizabeth Piper Deschenes ; Barbara Owen ; Jason Crow Document No.: 216950 Date Received: January 2007 Award Number: 2004-IJ-CX-0038 This report has not been published by the U.S. Department of Justice. To provide better customer service, NCJRS has made this Federally- funded grant final report available electronically in addition to traditional paper copies. Opinions or points of view expressed are those of the author(s) and do not necessarily reflect the official position or policies of the U.S. Department of Justice. This document is a research report submitted to the U.S. Department of Justice. This report has not been published by the Department. Opinions or points of view expressed are those of the author(s) and do not necessarily reflect the official position or policies of the U.S. Department of Justice. Final Report Recidivism among Female Prisoners: Secondary Analysis of the 1994 BJS Recidivism Data Set Grant # 2004-IJ-CX-0038 Submitted by: Elizabeth Piper Deschenes Department of Criminal Justice California State University Long Beach 1250 Bellflower Blvd. Long Beach, CA 90840-4603 Telephone 562/985-8567 Email: [email protected] Barbara Owen Jason Crow Department of Criminology California State University-- Fresno Fresno California 93740 Telephone: 559/278-5715 Email: [email protected] October 2006 This project was funded by Grant # 2004-IJ-CX-0038 from The National Institute of Justice, Data Resources Program 2004: Funding for the Analysis of Existing Data. -
Decision Making with Limited Feedback:Error Bounds for Recidivism
Decision making with limited feedback: Error bounds for recidivism prediction and predictive policing Danielle Ensign Sorelle A. Friedler Scott Neville University of Utah Haverford College University of Utah Carlos Scheidegger Suresh Venkatasubramanian University of Arizona University of Utah ABSTRACT These deployed models mostly use traditional batch-mode When models are trained for deployment in decision-making machine learning, where decisions are made and observed in various real-world settings, they are typically trained in results supplement the training data for the next batch. batch mode. Historical data is used to train and validate the However, the problem of feedback makes traditional batch models prior to deployment. However, in many settings, feed- learning frameworks both inappropriate and incorrect. Hiring back changes the nature of the training process. Either the algorithms only receive feedback on people who were hired, learner does not get full feedback on its actions, or the deci- predictive policing algorithms only observe crime in neigh- sions made by the trained model influence what future train- borhoods they patrol, and so on. Secondly, decisions made by ing data it will see. We focus on the problems of recidivism the system influence the data that is fed to it in the future. For prediction and predictive policing, showing that both prob- example, once a decision has been made to patrol a certain lems (and others like these) can be abstracted into a general neighborhood, crime from that neighborhood will be fed into reinforcement learning framework called partial monitoring. the training apparatus for the next round of decision-making. We then design algorithms that yield provable guarantees on In this paper, we model these problems in a reinforcement regret for these problems, and discuss the policy implications learning setting, and derive algorithms with provable error of these solutions. -
Recidivism Among Federal Offenders: a Comprehensive Overview
Recidivism Among Federal Offenders: A Comprehensive Overview UNITED STATES SENTENCING COMMISSION UNITED STATES SENTENCING COMMISSION ONE COLUMBUS CIRCLE, N.E. WASHINGTON, DC 20002 WWW.USSC.GOV Patti B. Saris Chair Charles R. Breyer Vice Chair Dabney L. Friedrich Commissioner Rachel E. Barkow Commissioner William H. Pryor, Jr. Commissioner Michelle Morales Ex Officio J. Patricia Wilson Smoot Ex Officio Kenneth P. Cohen Staff Director Glenn R. Schmitt Director Office of Research and Data March 2016 Kim Steven Hunt, Ph.D Senior Research Associate Robert Dumville Research Associate TABLE OF CONTENTS PART I INTRODUCTION 2 PART II SUMMARY OF KEY FINDINGS 4 PART III DESCRIPTION OF METHODOLOGY AND STUDY GROUP 6 Defining and Measuring Recidivism 7 Methodology 8 The Study Group 9 PART IV DETAILED RECIDIVISM FINDINGS 14 General Recidivism Rates 15 Most Serious Recidivism Offense 17 Recidivism and Criminal History 18 Recidivism and an Offender’s Federal Offense 20 Recidivism and Sentences Imposed 22 Recidivism and Offender Characteristics 23 PART V CONCLUSION 26 ENDNOTES 28 APPENDIX 34 i PART I Introduction This report provides a broad overview of key findings from the United States Sentencing Commission’s study of recidivism of federal offenders. The Commission studied offenders who were either released from federal prison after serving a sentence of imprisonment or placed on a term of probation in 2005. Nearly half (49.3%) of such offenders were rearrested within eight years for either a new crime or for some other violation of the condition of their probation or release conditions. This report discusses the Commission’s recidivism research project and provides many additional findings from that project.