Employment selection processes that use automated hiring systems based on machine learning are becoming increasingly commonplace. Meanwhile, concerns about algorithmic direct and indirect discrimination that result from such systems are front-and-center, and the technical solutions provided by the research community often systematically deviate from the principle of equal treatment to combat disparate or adverse impacts on groups based on protected attributes. Those technical solutions are now being used in commercially available automated hiring systems, potentially engaging in real-world discrimination. Algorithmic fairness and algorithmic non-discrimination are not the same. This article examines a conflict between the two: whether such hiring systems are compliant with EU non-discrimination law.

翻译：基于机器学习的自动化招聘系统在就业选拔过程中日益普及。与此同时，此类系统导致的算法直接歧视与间接歧视问题备受关注，而研究界提出的技术解决方案往往系统性地偏离平等待遇原则，未能有效消除基于受保护属性对群体造成的不利影响或差异化冲击。这些技术方案现已应用于商业化的自动化招聘系统，可能在实际场景中引发歧视。算法公平性与算法非歧视性并非同一概念。本文探讨二者之间的冲突：此类招聘系统是否符合欧盟非歧视法的规定。