Florida Uses BI Tech to Profile At-Risk Kids: Smart or Scary?

It sounded like your typical vendor press release, another in the long line of software vendor announcements last week: “Florida Department of Juvenile Justice (DoJJ) to Reduce Rate of Re-offenders with IBM Predictive Analytics.”

The Florida DoJJ seemingly had high hopes for the IBM SPSS analytics package it purchased, which, if all goes well, will enable administrators to better understand, predict the behaviors and properly assign rehabilitation programs for the 85,000 youths who enter Florida’s juvenile justice system every year.

As part of the orchestrated PR announcement, Mark Greenwald, chief of research and planning at Florida DoJJ, wrote a post on IBM’s Smarter Planet blog:

“Using this technology, we are confident our organization can improve its existing screening and placement process and intervene in juvenile lives earlier to help them become—and stay—law abiding citizens. Essentially, it will predict which youths will have a higher likelihood to reoffend. Using evidence-based interventions, we can direct youth toward treatment that will address their specific criminogenic needs. This gives us the opportunity to place individuals in specific programs, such as combating substance abuse or addressing mental health issues, creating personalized—versus generic—rehabilitation programs.

In addition, Bill Haffey, predictive analytics strategist for the public sector at SPSS, spoke with CivSource about the software.

“At the Department of Juvenile Justice, their interest has always been the same—to identify offenders who are likely to accelerate, or graduate, into the adult court system,” Haffey told CivSource. “In the past they’ve taken a uni-dimensional analysis. If a juvenile was in the system two or three times, there was a knee-jerk reaction to ‘watch out’ for that person. But there were other pieces of information that hadn’t been fully exploited in the past.” Those data points include: past offense history, home life environment, gang affiliation and peer associations, all of which could help predict which youths could have a higher likelihood to reoffend, according to the article. Haffey added that it is typically difficult to look at “any one of those factors because individually they mask the larger effects of their combined influence,” states the CivSource article.

To me, anyway, the DoJJ program—as I read the press release, the blog post and the interview—appeared to have merit: an application of technology to help an organizational (“business”) problem.

But to one Gizmodo blogger as well as the Techdirt website, the Florida DoJJ’s use of the IBM SPSS predictive analytic software is a very bad and dangerous idea. Both envisioned this move as a step toward the “precognitive crime prevention” featured in the movie Minority Report.

In fact, the Gizmodo blogger, Jesus Diaz, went so far as to make a loose connection between IBM’s cataloguing technology in the 1930s and the Holocaust. “No matter how you look at it,” Diaz writes, “cataloguing people—any kind of people—based on statistical predictive software, and then taking pre-empetive actions against them based on the results, is the wrong way to improve our society.”

On the popular and insightful Techdirt website, blogger Karl Bode urged some caution: “You still have to wonder how accurate these kinds of systems are and how independently verifiable the evidence will be. Can kids who feel they were unfairly, preemptively declared to be bad asses in 2014 see the ‘reliable’ source code?”

Blind faith in technology is certainly not a good strategy. But I have to disagree with any fear-mongering sentiments. In response to the mild outrage, I would offer these questions: Would you rather have Florida DoJJ administrators making these same serious decisions based solely on “gut feelings,” or potentially flawed Excel spreadsheets? Wouldn’t you rather have some data points upon which to base those critical decisions?

Instead of relying on a “watch out for that person” label, it seems much more logical and appropriate to allow for actual facts and correlative data pieces to help create a rehabilitation plan for the youth offenders.

Diaz himself writes this: “Other people will say that government officials already make these decisions based on reports and their own judgment. True. It seems that a computer program may be fairer than a human, right? Maybe. But at the end the interpretation of the data is always in the hands of humans (and the program itself is written by humans).”

No argument there. Of course, this distinction applies to any technology application. And in this case it’s this: Predictive software aids in decision making; it does not automate it.

The businessworld is clearly moving on from outdated spreadsheets, “from the gut” decisions and knee-jerk labeling. It’s called using BI software. The state of Florida’s Department of Juvenile Justice is just trying to keep up.

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