Kelly Hannah-Moffat (2010) Actuarial Sentencing: An “Unsettled” Proposition

(For Sept 2010 – University at Albany Symposium on Sentencing)
Kelly Hannah-Moffat, University of Toronto

Actuarial risk has both supporters and detractors who argue “against prediction” (Harcourt, 2007), cautioning law and policy makers about some of the assumptions and ambiguities of actuarial technologies. To what end could risk assessments be jurisprudentially relevant to sentencing for judges concerned with crime prevention, recidivism and effective interventions? In this context, a probabilistic statement of risk and systematic weighing of risk factors may help a judge craft a sentence and apply meaningful conditions. New risk configurations inherent in tools like the LSI are important not only for theorizing the concept of risk, but also for understanding new and evolving penal strategies (Maurutto and Hannah-Moffat, 2006). (…)

The uncritical acceptance of science and related risk technologies can jeopardize due process, produce disparities and discrimination, undercut proportionality, escalate the severity of sentences, and punish individuals for crimes that they have not committed. However, risk (and some evidence-based practices) may facilitate a reduction in penal populations, and over time lead to the application of different and perhaps more constructive interventions. Acknowledging this possibility, I remain concerned about how introductions of risk into sentencing will shape punishment and impact already disadvantaged and unmotivated or treatment-resistant defendants and further how the use of actuarial methods can accentuate the prejudices and biases that are built into law, punishment, and criminal law enforcement (cf. Harcourt, 2007). This discussion has prompted a number of questions for which there are presently insufficient answers: 

1. To what extent should risk predictions inform sentencing practices?
2. How should risk predictions be balanced with wider sentencing goals?
3. What is the impact of using risk prediction in conjunction with other sentencing guidelines (i.e., mandatory minimums) and priorities (i.e., due process, just desserts, etc.)?
4. Are the risk instruments used in given sentencing jurisdiction responsive to the populations to which they are applied?
5. Are the instruments used properly crafted to achieve their intended purposes? This question raises concerns about using risk instruments in sentencing without first considering their compatibility with broader sentencing jurisprudence and guidelines.
6. Are racialized populations disproportionately represented in risk categories?
7. Does risk-need assessment increase sentence uniformity?
8. How does risk assessment data compare with general population data?
9. What are the implications of not using the risk assessment device when tools exist? If a tool is used, then how does one reconcile conflicting understandings about how it should be used to predict and/or sentence? For example, some of the research supporting risk tools argues that the combination of actuarial scores with clinical judgments inevitably produces lower accuracy than actuarial scores alone,28 and that “unaided” clinical judgment is less accurate than actuarially aided judgments. This raised the interesting paradox of whether judges are, or even should be, concerned with the accurate prediction of recidivism and the legal relevance and weight of that information.
10. Given the technical and conceptual limits of risk, how and when can these tools be meaningfully used?

Hannah-Moffatt_RiskAssessment_000.pdf