Evaluación de sistemas de inteligencia artificial: métodos y prácticas en el contexto sociopolítico de américa latina y el caribe

Abstract

In the implementation of artificial intelligence systems, rigorous evaluation is crucial to ensure their effectiveness, fairness, and safety. This article examines the methods and practices for evaluating AI systems in the sociopolitical context of Latin America and the Caribbean, a region characterized by its cultural diversity and variability in regulatory and legal frameworks. The technical, ethical, and legal evaluation methods are analyzed, highlighting the need to adapt them to local contexts. Technical evaluation includes performance and robustness testing, while ethical evaluation addresses fairness and non-discrimination, and legal evaluation focuses on compliance with local data protection laws. Additionally, community participation practices, international collaboration, and professional training are discussed as strategies to strengthen the evaluation of AI systems in the region. Challenges include limited technological infrastructure and cultural diversity, but opportunities are also identified to develop innovative solutions tailored to local contexts. This analysis underscores the importance of a multidimensional and collaborative approach to ensure that AI systems benefit all communities in a fair and inclusive manner. Finally, future research lines are suggested to improve evaluation practices and promote equity in AI systems in Latin America and the Caribbean.