Definition
Actuarial justice is a mode of criminal justice that treats crime as a statistical aggregate to be managed, not a moral problem to be solved. Instead of asking why a particular person offended or how to reform them, it asks which categories of people present elevated risk and how those risks can be efficiently contained.
The framing comes from Malcolm Feeley and Jonathan Simon's account of a "new penology" emerging in the late twentieth century. Their argument: probation officers, parole boards, sentencing commissions, and police agencies increasingly behave like insurance adjusters, classifying populations and allocating supervision by score rather than by individual story.
Why it matters
How it works
The operational unit shifts from the individual to the group. Tools like recidivism scores, gang databases, and hotspot maps pool historical data, find correlates of future offending, and assign each case a risk band. Resources then follow risk: low-risk cases get minimal supervision, high-risk cases get incarceration, electronic tags, or intensive monitoring. The goal is not to change the offender but to keep the predicted harm within tolerable limits.
Critics argue this approach launders structural bias into seemingly neutral arithmetic. If past arrests are concentrated in poor or racialised neighbourhoods, any model trained on them will recommend more policing of those same neighbourhoods, generating fresh data that confirms the original pattern. Actuarial justice is therefore a useful diagnostic lens on contemporary punishment as much as a description of administrative practice.