Estrategias de diversidad e inclusión en procesos de reclutamiento asistidos por IA

The study critically explores the impact of artificial intelligence on recruitment processes, focusing on its ability to reproduce historical biases that affect employment diversity. Through a literature review of research and policy documents between 2013 and 2024, strategies aimed at mitigating algorithmic bias were identified, including fairness audits, use of balanced data, de-biasing techniques, and multidisciplinary team building. The findings reveal that no single measure is sufficient and that effective deployment requires a combination of technical practices and organizational frameworks committed to transparency and equity. It is concluded that the responsible adoption of AI in recruitment depends on articulating technological innovation with sound ethical principles, emphasizing the need for inclusive policies, auditable processes and the integration of diverse perspectives to ensure equitable opportunities in talent selection.