The use of data-driven decision support by public agencies is becoming more widespread and already influences the allocation of public resources. This raises ethical concerns, as it has adversely affected minorities and historically discriminated groups. In this paper, we use an approach that combines statistics and data-driven approaches with dynamical modeling to assess long-term fairness effects of labor market interventions. Specifically, we develop and use a model to investigate the impact of decisions caused by a public employment authority that selectively supports job-seekers through targeted help. The selection of who receives what help is based on a data-driven intervention model that estimates an individual's chances of finding a job in a timely manner and rests upon data that describes a population in which skills relevant to the labor market are unevenly distributed between two groups (e.g., males and females). The intervention model has incomplete access to the individual's actual skills and can augment this with knowledge of the individual's group affiliation, thus using a protected attribute to increase predictive accuracy. We assess this intervention model's dynamics -- especially fairness-related issues and trade-offs between different fairness goals -- over time and compare it to an intervention model that does not use group affiliation as a predictive feature. We conclude that in order to quantify the trade-off correctly and to assess the long-term fairness effects of such a system in the real-world, careful modeling of the surrounding labor market is indispensable.
翻译:公共机构对数据驱动决策支持的使用正在变得日益广泛,已经影响到公共资源分配。这引起了道德问题,因为它对少数群体和历史上受歧视的群体产生了不利影响。在本文件中,我们采用了一种结合统计和数据驱动方法与动态模型相结合的方法,以评估劳动力市场干预的长期公平影响。具体地说,我们制定并使用一种模式,调查公共就业当局通过有针对性的帮助有选择地支持求职者的决定的影响。选择谁得到什么帮助,这种模式基于数据驱动干预模式,该模式估计个人及时找到工作的机会,并依赖于描述与劳动力市场有关的技能在两个群体(如男性和女性)之间分布不均的人口的数据。干预模式没有完全掌握个人的实际技能,并且能够利用个人群体归属的知识来增加这种能力,从而利用受保护的属性来提高预测准确性。我们评估这一干预模式的动态 -- -- 尤其是与公平相关的问题和不同公平目标之间的取舍 -- -- 随着时间的推移,并将其与干预模式加以比较,该模式没有使用与劳动力市场相关的技能在两个群体(如男性和女性)之间分配不均匀的分布。干预模式,该干预模式可以不完全地利用群体之间的关联性,从而对市场进行量化。