Approximately 500,000 arrested individuals are detained in American jails at any given moment, a 400% increase since 1970. Over 95% of arrestees in the United States are subjected to some form of pretrial detention. Many of these people, often charged with minor crimes, spend weeks or months waiting for resolution of their cases in horrendous conditions. Much of this is due to a cash bail system that effectively incarcerates people because they are poor, with a disproportionate effect on people of color.
In Chapter 5 of his book Rehabilitating Criminal Justice, Chris Slobogin argues that a technology-fueled solution exists which could reduce rates of pretrial detention while addressing legitimate concerns about public safety.
“Risk assessment algorithms, if properly validated and properly used, can drastically decrease prison and jail populations without significantly increasing crime rates, by distinguishing between high and low risk individuals,” he writes.
Referencing his 2021 book Just Algorithms: Using Science to Reduce Incarceration and Inform a Jurisprudence of Risk, Slobogin demonstrates the value of existing risk-assessment instruments relying on research from jurisdictions across the country. These studies indicate that algorithmic tools would likely outperform judges’ ability to assess the risk of granting pretrial release to defendants.
“Presumptive use of risk assessment instruments. . . may be the single best way to simultaneously increase release rates, reduce racial disparities in pretrial decision-making, protect the public, and ensure released defendants return for trial,” he concludes.
“It is certainly more likely to achieve those goals than the current system’s reliance on cash bail and judicial seat-of-the-pants decision-making.”
Rehabilitating Criminal Justice, published by Cambridge University Press, publishes in March and is currently available for pre-order.
