审前风险评估工具的风险评估：纠纷、缓解策略和固有限制
A Risk Assessment of a Pretrial Risk Assessment Tool: Tussles, Mitigation Strategies, and Inherent Limits
摘要：
我们对公共安全评估（PSA）进行风险评估，这是一种在旧金山和其他司法管辖区使用的软件，用于协助法官决定被告是否需要在审判前被拘留。通过包括利益相关者访谈和使用理论框架在内的混合方法，我们展示了审前司法自动化的价值观。在确定了将决策委托给技术的价值影响后，我们阐述了PSA解决方案的优点和局限性，并提出了缓解策略。然后，我们起草了汉克斯树，一种新颖的算法方法，以审前司法，适应一些固有的限制，风险评估工具的设计。该模型将每个预测与相关的出错率配对，如果不确定性太高，则将决定权交给法官。通过明确说明出错率，汉克斯树旨在限制种族和性别之间的预测差异的影响，并促使法官对保留建议更加挑剔，因为他们经常带来高误报率。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
