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We perform a risk assessment of the Public Safety Assessment (PSA), asoftware used in San Francisco and other jurisdictions to assist judges indeciding whether defendants need to be detained before their trial. With amixed-methods approach including stakeholder interviews and the use oftheoretical frameworks, we lay out the values at play as pretrial justice isautomated. After identifying value implications of delegating decision makingto technology, we articulate benefits and limitations of the PSA solution, aswell as suggest mitigation strategies. We then draft the Handoff Tree, a novelalgorithmic approach to pretrial justice that accommodates some of the inherentlimitations of risk assessment tools by design. The model pairs everyprediction with an associated error rate, and hands off the decision to thejudge if the uncertainty is too high. By explicitly stating error rate, theHandoff Tree aims both to limit the impact of predictive disparity between raceand gender, and to prompt judges to be more critical of retentionrecommendations, given the high rate of false positives they often entail.

A Risk Assessment of a Pretrial Risk Assessment Tool: Tussles, Mitigation Strategies, and Inherent Limits