Machine predictions can cut crime by a quarter without growing jail populations

Evidence

This is not the only example of legal technology working for good. As discussed above, in San Francisco, AI is being used to blind police reports so that prosecutors cannot tell the race of defendants (Gecker, 2019). Jurisdictions across the country are using the Public Safety Assessment tool (PSA), which was designed to reduce bias in judicial decision-making. In assessing dangerousness, the tool takes into account age and history of criminal convictions, but it elides race, gender, employment background, where a defendant lives, and history of criminal arrests (Arnold Foundation, 2018). Finally, there is groundbreaking theoretical work showing that machine predictions can lead to drastically improved legal outcomes (Kleinberg et al., 2018). The authors found that their policy simulation would reduce crime by up to 25 percent without causing an increase in jail populations. Alternatively, it would be possible to keep crime rates steady while reducing jail populations by 42 percent. — Joseph Avery, Jim Sidanius, Joel Cooper, Gregory Davis, Amanda N., Bias in the Law, 1172

Categorization

• XREF: Connects to earlier scholarship on algorithmic bias and the PSA tool’s design tradeoffs between predictive accuracy and fairness variables.