Actuarial Risk Assessment and Human Rights: A Commentary

Abstract

Introduction In recent years, criminal justice professionals have increasingly endorsed actuarial measures of risk as the most reliable predictive instruments for decision making (Ericson and Haggerty 1997; Hannah-Moffat and Shaw 2001). Andrews and Bonta define the actuarial approach as involving criteria for decisions that are validated by (2003: 234). In a recent review of best practices in risk assessment, Bonta (2002) indicates that the first guideline for psychologists when assessing risk is to rely on empirically based actuarial risk instruments. The performance of judgement (i.e., determination of risk based on professional opinion and expertise) compared to actuarial risk assessment in predicting criminal behaviour is by now well documented (Bonta, Law, and Hanson 1998; Grove and Meehl 1996; Grove, Zald, Lebow, Snitz, and Nelson 2000). Some have even argued that failure to conduct actuarial risk assessment or consider its results is irrational, unscientific, unethical, and unprofessional (Grove and Meehl 1996; Quinsey, Harris, Rice, and Cormier 1998). In the criminal justice context, judgement frequently fails to consider criminogenic risk factors (i.e., factors that research has found to be associated with criminality) and too often relies on characteristics not associated with criminality and recidivism, resulting in or unsubstantiated decisions (both false positives and false negatives). Grove and Meehl go so far as to argue that the clinical brain is a poor substitute for an explicit regression equation or actuarial table. Humans simply cannot assign optimal to variables, and they are not consistently applying their own weights (1996: 315). They further suggest that judgement is unduly vulnerable to personal prejudice and bias. The movement toward using actuarial risk assessment has permeated the entire criminal justice system. Criminal justice professionals are increasingly familiar with the long list of high-performing actuarial risk assessment instruments (Bonta 2002) with impressive acronyms, such as PCL-R, LSI-R, VRAG, HRC-20, SONAR, RRASOR, and STATIC-99. A few provincial jurisdictions require probation officers to include actuarial risk assessment results in pre-sentence reports (Cole and Angus 2003). Judges frequently rely on actuarial risk assessments when handing down their sentences, and a high level of risk invariably results in harsher dispositions (Zinger and Forth 1998). Correctional authorities routinely depend on actuarial risk assessment to make decisions on security classification, institutional placement, programming, and conditional release (e.g., temporary absences, work releases). Parole boards typically require such assessments before rendering decisions with respect to parole or other forms of conditional release. For many psychologists working in criminal justice, and a few psychiatrists, actuarial risk instruments are a part of the daily work routine and preoccupations (Bonta 2002). Academic journals are filled with articles on the validity of specialized scales that attempt to predict various forms of recidivism (general, violent, sexual recidivism). More telling, perhaps, is the literature comparing the performance of different instruments. The debates surrounding scale performance are frequently heated (Gendreau, Goggin, and Smith 2002; Hemphill and Hare 2004). Those who have developed instruments that outperform their competitors also appear to feel a certain sense of pride and accomplishment (Pratt 2001). Moreover, developing an instrument may result in considerable profit and prestige and, in some rare instances, even celebrity (see The Corporation [Abbott and Achbar 2003], featuring Dr Hare's PCL-R [1991]). In addition to substantial royalties, some instruments may generate further revenues by requiring mandatory specialized training in their use, application, and interpretation (e. …