论文标题
预测法院对a养费的决定：避免法官做出的决策和不可理解的AI模型中的法律外因素
Predicting Court Decisions for Alimony: Avoiding Extra-legal Factors in Decision made by Judges and Not Understandable AI Models
论文作者
论文摘要
机器学习技术的出现使得获得了推翻传统法律实践的预测系统。但是，在法院判决中对决定因素的寻找并没有导致试图取代人类的系统，这使得有可能更好地了解法官执行的决策机制。通过在法国司法管辖区提出的离婚事项中使用大量法院判决，并查看允许分配a养费的变量，并定义其金额，我们试图确定法官所做的决定中是否可能存在法律外因素。从这个角度来看，我们提出了一个可解释的AI模型，该模型是通过将分类与随机森林和回归模型相结合的，作为现有决策量表或从业者创建的指导方针的补充工具。
The advent of machine learning techniques has made it possible to obtain predictive systems that have overturned traditional legal practices. However, rather than leading to systems seeking to replace humans, the search for the determinants in a court decision makes it possible to give a better understanding of the decision mechanisms carried out by the judge. By using a large amount of court decisions in matters of divorce produced by French jurisdictions and by looking at the variables that allow to allocate an alimony or not, and to define its amount, we seek to identify if there may be extra-legal factors in the decisions taken by the judges. From this perspective, we present an explainable AI model designed in this purpose by combining a classification with random forest and a regression model, as a complementary tool to existing decision-making scales or guidelines created by practitioners.
