Machine Learning Risk Assessments in Criminal Justice Settings

While a belief exists in the literature that deep learning will be applied to risk assessment in the future, the risks, lack of interpretability, and need for large training data sets currently outweigh the potential benefits.

“While a belief does exist in the literature that deep learning will be applied to risk assessment in the future [22], the risks, lack of interpretability [23], and need for large training data sets [24] currently outweigh the potential benefits.”

Deep learning has shown no additional predictive power in this particular problem space while suffering from additional needs for training data.

“Deep learning has shown no additional predictive power in this particular problem space while suffering from additional needs for training data [24], while exacerbating existing concerns regarding interpretability and transparency [33].”

Because of the disconnect between political and judicial priorities, risk assessment tools often take many years to develop, and their risk scores are often ignored by judges.

“Because of the disconnect between political and judicial priorities, risk assessment tools often take many years to develop [24], and their risk scores are often ignored by judges [55].”

Even where these tools might contribute to more fairness in the judicial process, the public is often skeptical and slow to accept tools that come with documented risks.

“Even where these tools might contribute to more fairness in the judicial process, the public is often skeptical and slow to accept tools that come with documented risks [24].”