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MONEYBALLING CRIMINAL JUSTICE Anne Milgram Vice President of Criminal Justice Laura and John Arnold Milgram.

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Presentation on theme: "MONEYBALLING CRIMINAL JUSTICE Anne Milgram Vice President of Criminal Justice Laura and John Arnold Milgram."— Presentation transcript:

1 MONEYBALLING CRIMINAL JUSTICE Anne Milgram Vice President of Criminal Justice Laura and John Arnold Milgram (twitter)

2 Why Moneyball?  New Jersey -Camden Police Department -State Division of Criminal Justice -Re-entry (DOL, DOC, Parole)  Baseball, Healthcare, Education, etc.

3 Criminal Justice  Critical decisions made every day: who should be arrested, who should be charged, who should be diverted, who should be detoxed, who should be in a mental health placement, who should be detained, who should be released, and how long should someone serve in jail.  Startling that we don’t use data and analytics already.  We are making these decisions now. But without benefit of understanding – at a fundamental level – how the system works and what can be done to improve public safety.  Most U.S. jurisdictions don’t know what risk individual defendants pose to society, what drives their CJ system, or what can be done to reduce crime.

4 CJ Stats  Huge impact on public safety, cost and efficiency, and fairness of the system.  Corrections costs are generally the second highest budget item in state budgets: -Cost of local criminal systems nationally estimated by DOJ at over $130 billion per year. -Cost of incarcerating people prior to trial is over $9 billion per year. -According to DOJ, 13 million jail admissions per year (10 million people). -FBI reports that less than 5% arrests nationwide are for crimes of violence.

5 Current Challenges  Key players: -Police -Prosecutors -Defenders -Courts -Jails, Prisons, Probation, Parole  Lack of data  Lack of data-sharing  Cultural hurdles

6 Equals =

7 What Should We Know?  Who is in?  What for?  How frequently are they returning?  What risk do they pose to society (to reoffend)?  What do they pose a risk to reoffend for (violent/non-violent)?  What works best and for whom?  What is the level of risk for each individual offender?  Who needs to be in b/c threat to public safety and who can be dealt with more effectively in community? The key is to reduce crime.

8 One Example: Risk  One critical example of where data can transform criminal justice: determining risk.  Prior to working in the CJ system I assumed that police, prosecutors, judges, jails make decisions based on risk.  National focus groups conducted in the past year showed us that the American public thinks so too.  Turns out we are all wrong.  Most jurisdictions don’t know what risk individual defendants pose to society, what drives their CJ system, or what can be done to reduce crime.

9 Risk in Practice  Of the approximately 3,300 localities nationwide, only about 300 use risk.  Current model of risk: -Lengthy -Complicated -Inefficient -Requires considerable resources that many jurisdictions don’t have  We believe data and technology can create a better tool: -More efficient -Just -Cost effective -Available to all localities, despite limited resources

10 LJAF Initiatives  Partnering with CfA, Louisville, and NYC: -Moneyballing criminal justice in 2013  Studying key questions: -Can we use data to design a simpler, more objective and efficient way to predict risk that a defendant poses to society -Looking at police citations, alternatives to incarceration, methods of supervision, and other means of trying to reduce crime  Building tools: -National model risk assessment tool for Courts -District Attorney risk assessment tool -Development of technology (simulation models, etc.)

11 Closing Thoughts  Our CJ system makes critical decisions every single day without knowing whether these decisions are the right ones.  We need to change that. Data can transform CJ just like it has transformed baseball, healthcare and education. We have to work on data, technology and culture.  Think about Nate Silver, who went from forecasting baseball to forecasting political elections. When he was recently asked about the predictive field that is most likely to be transformed by technology in the next fifty years, Silver responded: I've tried to specialize in fields where people aren't using metrics as much, so in baseball, kind of before the Moneyball era, or certainly in politics, where I think the average news story is not all that data driven. So I do think about something like maybe local government…in contrast to some big cities with stodgy old bureaucratic ways of doing things.


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