Against Prediction: Profiling, Policing, and Punishing in an Actuarial Age / Edition 1

by Bernard E. Harcourt

Overview

From routine security checks at airports to the use of risk assessment in sentencing, actuarial methods are being used more than ever to determine whom law enforcement officials target and punish. And with the exception of racial profiling on our highways and streets, most people favor these methods because they believe they’re a more cost-effective way to fight crime.

In Against Prediction, Bernard E. Harcourt challenges this growing reliance on actuarial methods. These prediction tools, he demonstrates, may in fact increase the overall amount of crime in society, depending on the relative responsiveness of the profiled populations to heightened security. They may also aggravate the difficulties that minorities already have obtaining work, education, and a better quality of life—thus perpetuating the pattern of criminal behavior. Ultimately, Harcourt shows how the perceived success of actuarial methods has begun to distort our very conception of just punishment and to obscure alternate visions of social order. In place of the actuarial, he proposes instead a turn to randomization in punishment and policing. The presumption, Harcourt concludes, should be against prediction.

Product Details

ISBN-13:	9780226316147
Publisher:	University of Chicago Press
Publication date:	12/15/2006
Edition description:	Reprint
Pages:	264
Product dimensions:	6.00(w) x 9.00(h) x 1.40(d)

About the Author

Bernard E. Harcourt is Isidor and Seville Sulzbacher Professor of Law at Columbia Law School and the director of the Columbia Center for Contemporary Critical Thought. 

Read an Excerpt

Against Prediction Profiling, Policing, and Punishing in an Actuarial Age
By BERNARD E. HARCOURT
THE UNIVERSITY OF CHICAGO PRESS Copyright © 2007 The University of Chicago
All right reserved.
ISBN: 978-0-226-31614-7



Chapter One Actuarial Methods in the Criminal Law

CASE 1. In Kansas, the sentencing commission is required by statute annually to prepare two-year projections of the expected adult prison population. When its projections exceed available prison-bed capacity, the commission has to identify ways to either reduce the number of inmates admitted to prison or adjust the length of their sentences. In fiscal year 2002, with dire projections of an unprecedented number of prisoners, the Kansas legislature followed the lead of California and Arizona and instituted mandatory drug abuse treatment in lieu of incarceration for a designated group of drug offenders convicted after November 1, 2003. Other states faced with similar problems, such as Louisiana and Alabama, have enacted early-release legislation. Those statutes make outright release from prison possible in order to alleviate overcrowding.

In general, candidates for early release or diversionary programs must satisfy strict risk-of-reoffending criteria. For example, in Kansas, to be eligible for drug treatment in lieu of incarceration, the offender must have been convicted of drug possession only. Drug sales or trafficking preclude diversion, as do prior violent felonies and posing a significant threat to public safety. To assess the latter, the Kansas legislature mandates that each candidate for treatment be subject to what they refer to as "a statewide, mandatory, standardized risk assessment tool." That risk-assessment tool, in Kansas, is the Level of Services Inventory-Revised-known in the business as the LSI-R-and the results of the assessment are incorporated into the presentence investigation report submitted to the sentencing judge. From November 2003 to mid-January 2004, 149 drug convicts in Kansas were diverted to treatment.

The LSI-R was developed in Canada in the late 1970s and is used today in nearly all of the United States and the Canadian provinces at some point in the postconviction process-for the security classifications of prison inmates, for levels of probation and parole supervision, or as a factor for determining eligibility for parole. In many states the LSI-R is administered for multiple purposes. It is championed as a versatile and cost-effective tool for predicting risk and assessing needs. So, for instance, in Pennsylvania the LSI-R score is a component of a number-based decision matrix for deciding whether to parole an inmate. In Washington state the Indeterminate Sentence Review Board, assigned responsibility for determining parole eligibility for all offenders who committed their crimes prior to July 1, 1984, uses the LSI-R. In North Dakota the parole board considers the results of the LSI-R when making its decisions to parole someone-along with the availability of treatment programs, the nature of the offense, the inmate's prior record, and an evaluation of how well the inmate did under the terms of any prior parole and probation supervision. In Alaska the parole board may give the LSI-R score up to 35 percent weight in its decision, and in Vermont the LSI-R is one of the primary factors in the decision of the parole board. In Oklahoma active supervision of parole cannot be terminated without an LSI-R score below a designated number.

The trend toward using prediction instruments in the parole context is visually dramatic, as shown in figure 1.1, which traces the historical use of such instruments by state parole authorities over the past hundred years. Illinois alone accounted for the only use of an actuarial instrument throughout the 1930s, '40s, and '50s. Ohio experimented with a risk-assessment tool in the 1960s, and California began using a prediction tool in the early 1970s-as did the federal government. While some states, such as Illinois and California, later stopped using actuarial methods when they abandoned parole, other states, such as Georgia, Iowa, Tennessee, South Carolina, Alabama, and Florida, began using risk-assessment tools in the late 1970s and early 1980s. Soon, many other states followed their lead-Missouri, Michigan, North Dakota, South Dakota, Washington, Arkansas, Colorado, Nevada, Maryland, Connecticut, New Jersey, Ohio, Vermont, Alaska, Idaho, Kentucky, Maine, Montana, Pennsylvania, Texas, Utah, and Delaware.

In 2004, twenty-eight states used risk-assessment tools to guide their parole determinations-approximately 72 percent of states that maintain an active parole system. As a leading parole authority association suggests, "In this day and age, making parole decisions without benefit of a good, research-based risk assessment instrument clearly falls short of accepted best practice."

CASE 2. The Internal Revenue Service receives approximately 130 million individual tax returns per year, but only has the resources to audit about 750,000 or 0.6 percent of those filings-about 1 in 170. In order to enhance its ability to detect tax evasion, the IRS has developed a complex, top-secret computer algorithm that predicts likely cheating electronically. Each return is fed into a computer in Martinsburg, West Virginia, and the computer assigns a score based on the algorithm-an algorithm guarded like the Coca-Cola formula. "The higher the score, the more likely a return will be selected for an audit," the IRS explains.

The algorithm is known as the Discriminant Index Function, or DIF. The DIF is based on multiple-regression analysis of past audits intended to identify the key factors that are most likely to indicate tax fraud. The DIF was last updated in 1992 based on a regression analysis of approximately 50,000 tax returns that had been randomly audited in 1988. The DIF is an expense-based scoring model that is based on the actual items on a tax return, rather than on failures to report items. (Another filter, the UIDIF, was developed around 2000 to pick up returns that fail to report items reported on other forms, such as W-2s, 1099s, and 1098s.)

The DIF compares the tax return under review with average returns in the same income bracket and profession, and identifies outliers. It assigns a number value to suspicious items on the tax return and then produces a score that represents the estimated probability of noncompliance. Typical items that may raise a red flag-according to leaked information-include high, above-average levels of itemized deductions and Schedule C filings. When the DIF score exceeds the IRS target, the tax return is reviewed manually by an IRS agent in order to determine whether it should be audited. Depending upon the problems detected, the return will be sent to an IRS Service Center or an IRS district office. Returns that fit the profile are the most likely to be examined. The IRS uses the DIF system to select around 20-30 percent of the tax returns that are audited each year in the United States.

CASE 3. In September 1994, the governor of Virginia, George Allen, called a special session of the Virginia legislature to consider sweeping reforms to the state's felony sentencing system. Under the motto of "truth-in-sentencing," the governor and legislature abolished the existing parole system and imposed mandatory sentence-completion requirements. Convicted felons were now required to complete at least 85 percent of their prison sentences. And the sentences were lengthened: the reform package required that violent offenders serve prison terms two to six times longer than before. The governor and legislature also established a sentencing commission, the Virginia Criminal Sentencing Commission, to develop and eventually administer a new set of discretionary sentencing guidelines that would channel judicial discretion in sentencing.

Along with these reforms, the Virginia governor and legislature placed a new emphasis on using empirically based, actuarial risk-assessment instruments. The Virginia legislature directed the new sentencing commission to develop a first actuarial instrument in the context of nonviolent offenders who could be diverted from the prison system at low risk. Specifically, the commission was asked to "study the feasibility of using an empirically based risk assessment instrument to select 25% of the lowest risk, incarceration bound, drug and property offenders for placement in alternative (nonprison) sanctions." After examining a random sample of more than two thousand drug, fraud, and larceny cases, the commission produced an actuarial instrument-the Risk Assessment Instrument-that was put into effect in pilot sites in 1997. A follow-up study by the National Center for State Courts of 555 diverted offenders in six judicial circuits in Virginia concluded that the program was a success and recommended the statewide expansion of risk assessment at the sentencing stage.

The legislature then asked the commission in 1999 to develop an actuarial risk-assessment instrument to predict recidivism for sex offenders in order to enhance their sentences under the voluntary guidelines. The commission conducted extensive empirical analyses of felony sex offenders convicted in the Virginia circuit courts. Taking a random sample of 579 felony sex-offenders released from prison between 1990 and 1993, the commission reviewed narrative accounts in pre- and postsentence investigation reports, rap sheets, criminal background records, and other information on the offender and the offense. After two years of data collection and data analysis, the commission produced an actuarial risk-assessment tool.

Virginia's Sex Offender Risk Assessment instrument became operational on July 1, 2001, and since then has been incorporated into the sentencing guideline system for sex offenders. The instrument uses a set matrix to produce a numeric score that is used to classify convicted individuals into one of four risk levels. To calculate the numeric score, judges and sentencing officials are referred to a simple, one-page, fill-in-the-blanks grid. In rape cases, the grid takes account of eight factors concerning the offender and the offense, including the age, education, and employment record of the convict; his relationship to the victim; the location of the offense; and his prior arrest, incarceration, and treatment record. In lesser sexual assault cases (including, for instance, molestation, but excluding "bestiality, bigamy, non-forcible sodomy, and prostitution"), a separate grid asks one additional question concerning the aggravated nature of the sexual battery. In all rape and other sexual assault cases, the responsible criminal justice official fills in the blanks on the worksheet and obtains a risk score that then translates into a risk level. Figure 1.2 shows an example of the grid in the rape cases.

Possible scores on the risk-assessment tool range from 0 to 65. For anyone scoring 28 or more, the sentencing guidelines have been adjusted to ensure that a term of imprisonment will always be recommended. In addition, any score above 28 results in an increased maximum sentence recommendation (without affecting the minimum recommendation). The increased sentence recommendation adjustments, based on those scores, are as follows:

0-27 No adjustment 28-33 Level 3 50% increase in upper end of the guideline range 34-43 Level 2 100% increase in upper end of the guideline range 44+ Level 1 300% increase in upper end of the guideline range

These risk levels are meant to "identify those offenders who, as a group, represent the greatest risk for committing a new offense once released back into the community."

Virginia courts have begun to rely on the risk-assessment adjustment to enhance the sentences of convicted sex offenders. In 2004, 233 offenders were convicted of rape in Virginia. Of those, 118, or 50.6 percent, were classified as level 1, 2, or 3 offenders, receiving enhanced sentencing recommendations; the other half had scores under 28 and therefore received no recommended adjustment. Of the offenders classified as level 1, 2, or 3, approximately 20 percent actually received enhanced sentences as a result of their higher-risk status. Of the 166 lesser sexual assault offenders with level 1, 2, or 3 risk, 16.26 percent received enhanced sentences. In addition, in those lesser sexual assault cases, judges followed the recommendation for incarceration in 75 percent of the cases-resulting in a prison sentence rather than probation.

Virginia has also led the country in the area of civil commitment of "sexually violent predators"-a term of art in today's criminal justice system that refers to sex offense recidivists who have been released from prison. John Monahan, a leading expert in the development and use of risk-assessment instruments, notes, "Virginia's sexually violent predator statute is the first law ever to specify, in black letter, the use of a named actuarial prediction instrument and an exact cut-off score on that instrument."

That statute, Virginia's Sexually Violent Predators Act (SVPA), enacted in April 2003, provides for the civil commitment of sex offenders who have been convicted of a sexually violent offense and who are deemed likely to engage in sexually violent acts in the future. Offenders are identified for possible commitment based on an actuarial instrument, the Rapid Risk Assessment for Sex Offense Recidivism (RRASOR). This instrument is explicitly mentioned in the SVPA, which directs the commissioner of the Virginia Department of Corrections to identify for review all prisoners about to be released "who receive a score of four or more on the Rapid Risk Assessment for Sexual Offender Recidivism or a like score on a comparable, scientifically validated instrument." The RRASOR consists of four items, scored as shown in table 1.1. The RRASOR score is the sum of the four items. As John Monahan explains, the RRASOR was based on an empirical study of male offenders in Canada. A "score of 4 or more on the RRASOR was associated with a 5-year sex offense recidivism rate of 37 percent and a 10-year sex offense recidivism rate of 55 percent."

The RRASOR is just one among a rash of new actuarial instruments that are intended to predict future sexual violence. Other instruments that have recently hit the market include the more comprehensive Static-99, which builds on the RRASOR; the Violence Risk Appraisal Guide (VRAG); the Hare Psychopathy Checklist-Revised (PCL-R); the Minnesota Sex Offender Screening Tool (MnSOST-R); the Sex Offender Risk Appraisal Guide (SORAG); the Sexual Violence Risk-20 (SVR-20); and the HCR-20-as well as, for the first time (released in 2005), violence risk-assessment software called the Classification of Violence Risk (COVR).

These new actuarial instruments have become increasingly popular in civil commitment statutes for sexually violent predators. As Carol Steiker notes, these statutes "were preceded by earlier 'sexual psychopath' or 'psychopathic personality' statutes, which were enacted in a large number of states between 1930 and 1960, but which mostly had been repealed or had fallen into desuetude by 1990." That trend was rapidly reversed in the 1990s, first in Washington state in 1990 and then with a rash of statutes modeled on Washington's. The most notorious of these statutes is the Kansas Sexually Violent Predator Act, which led to the United States Supreme Court's decision in Kansas v. Hendricks (1997) upholding such statutes against constitutional challenge. By 2004, sixteen states had enacted legislation similar to the Kansas statute. Of those sixteen, in fact, fourteen enacted such laws in the 1990s. For 2004, "1,632 people have been adjudicated to be sexually violent predators and are currently confined in psychiatric facilities, with a further 846 people hospitalized for evaluation and currently awaiting trial for commitment as sexually violent predators."

CASE 4. In the early 1970s, DEA agents John Marcello and Paul Markonni started identifying the common characteristics of illegal drug couriers disembarking from planes at U.S. airports. "The majority of our cases, when we first started," Markonni explains, "[were] ... based on information from law enforcement agencies or from airline personnel. And as these cases were made, certain characteristics were noted among the defendants." Those characteristics eventually became known as the drug-courier profile, first implemented in a surveillance and search program at the Detroit airport in the fall of 1974.

(Continues...)

Excerpted from Against Prediction by BERNARD E. HARCOURT Copyright © 2007 by The University of Chicago. Excerpted by permission.
All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the publisher.
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Table of Contents

Prologue
Chapter 1. Actuarial Methods in the Criminal Law
 
Part I. The Rise of the Actuarial Paradigm
Chapter 2. Ernest W. Burgess and Parole Prediction
Chapter 3. The Proliferation of Actuarial Methods in Punishing and Policing
 
Part II. The Critique of Actuarial Methods
Chapter 4. The Mathematics of Actuarial Prediction: The Illusion of Efficiency
Chapter 5. The Ratchet Effect: An Overlooked Social Cost
Chapter 6. The Pull of Prediction: Distorting Our Conceptions of Just Punishment
 
Part III. Toward a More General Theory of Punishing and Policing
Chapter 7. A Case Study on Racial Profiling
Chapter 8. Shades of Gray
Chapter 9. The Virtues of Randomization
 
Acknowledgments
Appendix A: Retracing the Parole-Prediction Debate and Literature
Appendix B: Mathematical Proofs Regarding the Economic Model of Racial Profiling
Notes
References
Index

Editorial Reviews

"As debate on profiling and terrorism grows sharper. . . . Harcourt's book will remain essential reading for those who wish to look past the chestnuts of stale debate on crime and policing, and to see with fresh eyes the problems of the criminal law."

New York Law Journal - Aziz Huq

"Harcourt welds normative and analytic arguments about risks and actuarial approaches to policing and criminal justice in a novel and readable fashion. This deserves a wide hearing among scholars and students interested in risk, actuaruarial logic and new modes of governance through crime control."

Surveillance and Society - Kevin Stenson

"Against Prediction is inspiring in its breadth of erudition, from mathematics to philosophy, sociology, and history, and persuasive in its impassioned and provocative argument. . . . If we want to break the hold that racialist thinking has on criminal law, there is no better place to begin than the apparently neutral actuarialism of the new penology."

Law & Social Inquiry - Ariela Gross

"Against Prediction convincingly argues that the use of economic actuarial methods—predicting individual criminal likelihood based on the quantifiable characteristics of groups to which one belongs—is fundamentally flawed. . . . That we fail to see the harms of prediction, and that we proudly aspire to some quixotic goal of corrective 'efficiency' is to our collective shame as much as Against Prediction is to Harcourt's credit."

Peter Moskosn Journal of Sociology

"In Against Prediction, Bernard Harcourt stresses that while the benefits of actuarial predictions have been widely touted, certain costs have been largely overlooked. Indeed, actuarial prediction can under some circumstances actually increase crime, and generate morally problematic social wounds on the profiled classes that might outweigh the benefits even if crime is reduced. Once again, Harcourt has challenged the conventional wisdom in criminal justice policy, and offered an indictment to the practice of actuarial prediction that policymakers, scholars and concerned citizens will have to fully consider."

John J. Donohue III

"Bernard Harcourt has never had an uninteresting thought, or made an argument that does not provoke or engage or delight or enlighten—or do all of those things simultaneously."

Malcolm Gladwell

"This is a creative, provocative, well-researched argument against current practice in sentencing, parole discrimination, and investigative profiling. Harcourt makes the case that a century of social science-inspired thinking about punishment and profiling should be cast out in favor of randomness. It is a position that will be dismissed by many as politically impractical, if not absurd. But that is often the immediate fate of revolutionary ideas."

Jack Katz

"[These] arguments should be studied by anyone who is considering  advocating, or utilizing, formal predictive methods in the domain of law enforcement."

Howard Journal - David Canter

"[Harcourt] has produced a book of such exceptional quality that this reviewer can only describe his offering as not only a welcome breath of fresh air on profiling, but urgent, required reading for all students of criminology, criminal justice, and, of course, profiling in all its forms. . . . This is scholarly analysis of the bases of actuarial criminal profiling at its very best and is an outstanding book. A new benchmark in the field."

Review of Policy Research - John Horgan

"Those whose focus is on behavioral and attitudinal studies should read this book. Why? It is counterintuitive. It offers challenging assumptions. It raises questions about social discrimination."

Law and Politics Book Review - David S. Mann

"Bernard Harcourt has never had an uninteresting thought, or made an argument that does not provoke or engage or delight or enlighten--or do all of those things simultaneously."

--Malcolm Gladwell (8/28/2006 12:00:00 AM)

"In Against Prediction, Bernard Harcourt stresses that while the benefits of actuarial predictions have been widely touted, certain costs have been largely overlooked. Indeed, actuarial prediction can under some circumstances actually increase crime, and generate morally problematic social wounds on the profiled classes that might outweigh the benefits even if crime is reduced. Once again, Harcourt has challenged the conventional wisdom in criminal justice policy, and offered an indictment to the practice of actuarial prediction that policymakers, scholars and concerned citizens will have to fully consider."

--John J. Donohue III, Leighton Homer Surbeck Professor of Law, Yale Law School (8/28/2006 12:00:00 AM)

"This is a creative, provocative, well-researched argument against current practice in sentencing, parole discrimination, and investigative profiling. Harcourt makes the case that a century of social science-inspired thinking about punishment and profiling should be cast out in favor of randomness. It is a position that will be dismissed by many as politically impractical, if not absurd. But that is often the immediate fate of revolutionary ideas."

--Jack Katz, University of California, Los Angeles (8/28/2006 12:00:00 AM)

"Against Prediction convincingly argues that the use of economic actuarial methods--predicting individual criminal likelihood based on the quantifiable characteristics of groups to which one belongs--is fundamentally flawed. . . . That we fail to see the harms of prediction, and that we proudly aspire to some quixotic goal of corrective 'efficiency' is to our collective shame as much as Against Prediction is to Harcourt's credit."--Peter Moskos "American Journal of Sociology"

"Against Prediction is inspiring in its breadth of erudition, from mathematics to philosophy, sociology, and history, and persuasive in its impassioned and provocative argument. . . . If we want to break the hold that racialist thinking has on criminal law, there is no better place to begin than the apparently neutral actuarialism of the new penology."--Ariela Gross "Law & Social Inquiry"

"[Harcourt] has produced a book of such exceptional quality that this reviewer can only describe his offering as not only a welcome breath of fresh air on profiling, but urgent, required reading for all students of criminology, criminal justice, and, of course, profiling in all its forms. . . . This is scholarly analysis of the bases of actuarial criminal profiling at its very best and is an outstanding book. A new benchmark in the field."--John Horgan "Review of Policy Research"

"[These] arguments should be studied by anyone who is considering advocating, or utilizing, formal predictive methods in the domain of law enforcement."--David Canter "Howard Journal"

"As debate on profiling and terrorism grows sharper. . . . Harcourt's book will remain essential reading for those who wish to look past the chestnuts of stale debate on crime and policing, and to see with fresh eyes the problems of the criminal law."--Aziz Huq "New York Law Journal" (5/25/2007 12:00:00 AM)

"Harcourt welds normative and analytic arguments about risks and actuarial approaches to policing and criminal justice in a novel and readable fashion. This deserves a wide hearing among scholars and students interested in risk, actuaruarial logic and new modes of governance through crime control."--Kevin Stenson "Surveillance and Society"

"Those whose focus is on behavioral and attitudinal studies should read this book. Why? It is counterintuitive. It offers challenging assumptions. It raises questions about social discrimination."--David S. Mann "Law and Politics Book Review"

From the Publisher

"Against Prediction convincingly argues that the use of economic actuarial methods—predicting individual criminal likelihood based on the quantifiable characteristics of groups to which one belongs—is fundamentally flawed. . . . That we fail to see the harms of prediction, and that we proudly aspire to some quixotic goal of corrective 'efficiency' is to our collective shame as much as Against Prediction is to Harcourt's credit."

American Journal of Sociology - Peter Moskos

"[These] arguments should be studied by anyone who is considering advocating, or utilizing, formal predictive methods in the domain of law enforcement."

— David Canter

Howard Journal

"Harcourt welds normative and analytic arguments about risks and actuarial approaches to policing and criminal justice in a novel and readable fashion. This deserves a wide hearing among scholars and students interested in risk, actuaruarial logic and new modes of governance through crime control."—Kevin Stenson, Surveillance and Society

— Kevin Stenson

Surveillance and Society

"Against Prediction is inspiring in its breadth of erudition, from mathematics to philosophy, sociology, and history, and persuasive in its impassioned and provocative argument. . . . If we want to break the hold that racialist thinking has on criminal law, there is no better place to begin than the apparently neutral actuarialism of the new penology."

— Ariela Gross

Law & Social Inquiry

"Those whose focus is on behavioral and attitudinal studies should read this book. Why? It is counterintuitive. It offers challenging assumptions. It raises questions about social discrimination."

— David S. Mann

Law and Politics Book Review

"The book is an excellent and convincing treatise against assuming that an individual's actions are predicted by group behavior. . . . Against Prediction convincingly argues that the use of economic actuarial methods--predicting individual criminal likelihood based on the quantifiable characteristics of groups to which one belongs--is fundamentally flawed. . . . That we fail to see the harms of prediction, and that we proudly aspire to some quixotic goal of corrective 'efficiency' is to our collective shame as much as Against Prediction is to Harcourt's credit."

— Peter Moskos

American Journal of Sociology

"As debate on profiling and terrorism grows sharper. . . . Harcourt's book will remain essential reading for those who wish to look past the chestnuts of stale debate on crime and policing, and to see with fresh eyes the problems of the criminal law."—Aziz Huq, New York Law Journal

— Aziz Huq

New York Law Journal

"Bernard Harcourt has never had an uninteresting thought, or made an argument that does not provoke or engage or delight or enlighten—or do all of those things simultaneously."

Malcolm Gladwell

"Against Prediction is inspiring in its breadth of erudition, from mathematics to philosophy, sociology, and history, and persuasive in its impassioned and provocative argument. . . . If we want to break the hold that racialist thinking has on criminal law, there is no better place to begin than the apparently neutral actuarialism of the new penology."

— John Horgan

Review of Policy Research