劳动力选择过程中算法歧视的法律分析
Análisis jurídico de la discriminación algorítmica en los procesos de selección laboral
摘要：
在处理工作申请时使用机器学习系统使这一过程变得敏捷和高效，但同时也在平等、可靠性和透明度方面产生了问题。在本文中，我们解释了ML在美国工作选择过程中的一些用途，并提出了一些已经发现的种族和性别偏见。实际上和法律上都存在阻碍发现和分析这些偏见的障碍。从法律角度如何处理算法歧视也不清楚。一个可能的分析工具是由美国的不同影响的理论，但我们显示了一些局限性和问题时，适应其他法律制度，如哥伦比亚法律。最后，我们提供了一些算法歧视的法律分析应该提供的必要条件。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
