Intersection of reliable AI with Labor Law. A legal and technical study from a tripartite taxonomy

Main text in Spanish.

This paper explores the intersection between Artificial Intelligence (AI) and labor law, focusing on the impact of AI technologies in the workplace from technical and legal perspectives. To do so, it uses a tripartite taxonomy that differentiates between the pre-implementation and post-implementation stages that make up the life cycle of an AI system, the elements that make up such systems and the requirements demanded for an AI to be qualified as reliable. This study highlights the main legal obligations and ethical principles established by the High-Level Expert Group on AI (HLEG) and the AI Regulation, which determine the requirements that an AI must meet to be considered trustworthy, such as human oversight, technical soundness, privacy and data management, transparency, diversity, non-discrimination and fairness, social and environmental well-being, and accountability. In addition, it examines how these requirements intersect with labor law. Finally, this paper is accompanied by an example and a table of equivalencies that should facilitate the understanding of the more complex concepts.