The Florida Department of Juvenile Justice is set to become the first state agency to conduct risk assessments using predictive analytics, a process that uses huge collections of data to predict outcomes and patterns.

It’s the sort of news that, on its face, excites at best a handful of stat geeks. But the decision could have major implications for providers of community-based juvenile justice services.

The research that prompted Florida’s decision suggests that significantly fewer juveniles would be slated for residential placements or incarceration under the new process. The new predictive model has superior ability to predict recidivism while also designating far fewer youth in risk categories that often lead to out-of-home placements.

The planned move appears to pave the way for reduced incarceration and increased spending on other alternatives without increased risk to the community.

From the paper co-written by the agency and a company called Algorhythm, analyzing the Florida research:

“Sizable reductions in residential care placements could lead to significant short-and long-term cost savings for the state and/or a freeing up of financial resources to be re-invested in preventative or community-based care.”

“The use of predictive analytics and machine learning will be a game changer in juvenile justice risk assessment,” said Algorhythm consultant Ira Schwartz, who led the federal Office of Juvenile Justice and Delinquency Prevention from 1979 to 1981. “Imagine what implications this has around the country.”

For more on this article from the Chronicles of Social Change by John Kelly, please see the link:  https://chronicleofsocialchang...-incarceration/10505