1:00 PM
Employers, landlords, and volunteer organizations routinely conduct criminal background checks to identify and filter candidates who might be deemed too risky to hire, rent to, or participate in volunteer opportunities. Results from these background checks are often used to justify barring people with convictions from those activities for a set period of time. Given that roughly 30 percent of people in the United States have criminal histories, exclusions resulting from background checks can foreclose opportunities for many. But what if it was possible to show that some people pose a low risk of recidivism?
Together with his RAND colleagues, Dr. Shawn Bushway has created the reset principle, which provides a foundation for risk-assessment models that could help identify people whose risk of recidivism has declined. The reset principle requires that a person's risk be estimated when a background check is conducted rather than at the time of last interaction with the criminal justice system.
The reset principle states that any risk prediction model must be able to update risk estimates, i.e., be "reset" at the time of a person's criminal background check. This principle—and risk-prediction models that satisfy it—account for the time a person has spent free in the community without a conviction, a hugely important signal of recidivism risk that may speak to their employability. The talk will emphasize the complexity of predicting risk and the need for careful consideration of multiple factors when doing so. The talk will also identify opportunities for policymakers to guide the development and use of these methods in the future.
Speakers
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Dr. Shawn Bushway