Stevenson Megan T, Slobogin Christopher
Antonin Scalia Law School, George Mason University, Fairfax, VA, USA.
Vanderbilt University Law School, Nashville, TN, USA.
Behav Sci Law. 2018 Sep;36(5):638-656. doi: 10.1002/bsl.2384.
At sentencing, youth can be considered both a mitigating circumstance because of its association with diminished culpability, and an aggravating circumstance because of its association with crime risk. In theory, judges and parole boards can recognize this double-edged sword phenomenon and balance the mitigating and aggravating effects of youth. But when sentencing authorities rely on algorithmic risk assessments, a practice that is becoming increasingly common, this balancing process may never take place. Algorithmic risk assessments often place heavy weights on age in a manner that is not fully transparent - or, in the case of proprietary "black box" algorithms, not transparent at all. For instance, our analysis of one of the leading black-box tools, the COMPAS Violent Recidivism Risk Score, shows that roughly 60% of the risk score it produces is attributable to age. We argue that this type of fact must be disclosed to sentencing authorities in an easily interpretable manner so that they understand the role an offender's age plays in the risk calculation. Failing to reveal that a stigmatic label such as "high risk of violent crime" is due primarily to a defendant's young age could lead to improper condemnation of a youthful offender, especially given the close association between risk labels and perceptions of character and moral blameworthiness.
在量刑时，青少年既可能因其与罪责减轻相关联而被视为从轻情节，又可能因其与犯罪风险相关联而被视为从重情节。从理论上讲，法官和假释委员会能够认识到这种双刃剑现象，并权衡青少年因素的从轻和从重影响。但当量刑机构依赖算法风险评估（这种做法正变得越来越普遍）时，这种权衡过程可能根本不会发生。算法风险评估往往以一种不完全透明的方式（或者在专有“黑箱”算法的情况下，完全不透明）高度重视年龄因素。例如，我们对一种领先的黑箱工具COMPAS暴力再犯风险评分的分析表明，它所产生的风险评分中约60%归因于年龄。我们认为，这类事实必须以易于解释的方式告知量刑机构，以便他们了解犯罪者年龄在风险计算中所起的作用。如果不揭示诸如“暴力犯罪高风险”这样的污名化标签主要是由于被告年龄小所致，可能会导致对年轻犯罪者的不当定罪，尤其是考虑到风险标签与性格认知和道德应受谴责性之间的紧密联系。
