论文标题
对审前风险评估工具的风险评估：争吵，缓解策略和固有限制
A Risk Assessment of a Pretrial Risk Assessment Tool: Tussles, Mitigation Strategies, and Inherent Limits
论文作者
论文摘要
我们对公共安全评估（PSA）进行风险评估，该评估是旧金山和其他司法管辖区使用的软件，以帮助法官在审判前是否需要拘留被告。采用混合方法方法，包括利益相关者访谈和使用理论框架，我们将其在审前司法自动化时提出了作用。在确定了将决策委托对技术的委托产生的含义之后，我们阐明了PSA解决方案的收益和局限性，并建议缓解策略。然后，我们起草了缩写树，这是一种新颖的算法方法，用于预审司法，可以通过设计来适应风险评估工具的一些固有局限性。模型将每个预测与相关的错误率配对，如果不确定性太高，则将决定交给法官。通过明确说明错误率，缩小树旨在限制种族和性别之间的预测差异的影响，并促使法官更批评保留建议，因为他们经常需要的假阳性率很高。
We perform a risk assessment of the Public Safety Assessment (PSA), a software used in San Francisco and other jurisdictions to assist judges in deciding whether defendants need to be detained before their trial. With a mixed-methods approach including stakeholder interviews and the use of theoretical frameworks, we lay out the values at play as pretrial justice is automated. After identifying value implications of delegating decision making to technology, we articulate benefits and limitations of the PSA solution, as well as suggest mitigation strategies. We then draft the Handoff Tree, a novel algorithmic approach to pretrial justice that accommodates some of the inherent limitations of risk assessment tools by design. The model pairs every prediction with an associated error rate, and hands off the decision to the judge if the uncertainty is too high. By explicitly stating error rate, the Handoff Tree aims both to limit the impact of predictive disparity between race and gender, and to prompt judges to be more critical of retention recommendations, given the high rate of false positives they often entail.
