论文标题
AnálisisjurídicodelaIndiminaciónAlgorítmicaen los procesos deselecciónLaboral
Análisis jurídico de la discriminación algorítmica en los procesos de selección laboral
论文作者
论文摘要
在处理工作应用中，使用机器学习系统使过程变得敏捷和高效，但与此同时，它在平等，可靠性和透明度方面造成了问题。在本文中，我们解释了ML在美国的工作选择过程中的一些用途，并提出了一些已检测到的种族和性偏见。有实际和法律障碍会阻碍对这些偏见的检测和分析。还不清楚如何从法律的角度处理算法歧视。美国对不同影响的美国学说提供了一种可能的分析工具，但是当适应其他法律制度（例如哥伦比亚法律）时，我们表明了它的一些局限性和问题。总而言之，我们提供了一些对算法歧视的法律分析应提供的逃避者。
The use of machine learning systems in processing job applications has made the process agile and efficient, but at the same time it has created problems in terms of equality, reliability and transparency. In this paper we explain some of the uses of ML in job selection processes in the United States, and we present some the racial and sexual biases that have been detected. There are both practical and legal obstacles that impede the detection and analysis of these biases. It is also unclear how to approach algorithmic discrimination from a legal point of view. A possible analytical tool is provided by the American doctrine of Disparate Impact, but we show some of its limitations and problems when adapted to other legal systems, such as Colombian law. To conclude, we offer some desiderata that any legal analysis of algorithmic discrimination should provide.
