Safe Policy Learning through Extrapolation: Application to Pre-trial Risk Assessment
通过外推进行安全政策学习：审前风险评估应用
Algorithmic recommendations and decisions have become ubiquitous in today’s society. Many of these data-driven policies, especially in the realm of public policy, are based on known, deterministic rules to ensure their transparency and interpretability. We examine a particular case of algorithmic pre-trial risk assessments in the US criminal justice system, which provide deterministic classification scores and recommendations to help judges make release decisions. Our goal…