El Rol de la Inteligencia Artificial en la Ciencia de Datos: Perspectivas Teóricas y Desafíos Emergentes

Anthony JeanPaul Reyes Risco; Juan Aurelio De La Cruz Gamarra; Marcelino Torres Villanueva

doi:10.48168/innosoft.s23.a208

Anthony JeanPaul Reyes Risco Universidad Nacional de Trujillo https://orcid.org/0009-0003-9268-2001
Juan Aurelio De La Cruz Gamarra Universidad Nacional de Trujillo
Marcelino Torres Villanueva Universidad Nacional de Trujillo

DOI: 10.48168/innosoft.s23.a208

PURL: 42411/s23/a208

ARK: ark:/42411/s23/a208

Palabras clave: AutoML, Big Data, Ciencia de Datos, Ética algorítmica, Inteligencia Artificial, Modelos Predictivos

Resumen

El artículo exploró cómo la Inteligencia Artificial (IA) y la Ciencia de Datos han revolucionado la creación y análisis de información al integrar metodologías avanzadas que superan las barreras tradicionales en la interpretación de datos complejos. Se abordaron conceptos fundamentales y desafíos técnicos y éticos actuales, destacando la automatización del ciclo de vida analítico mediante AutoML, la implementación de modelos explicables y la gestión de sesgos algorítmicos. La investigación examinó también las limitaciones de la IA en el procesamiento de datos no estructurados y su interacción con tecnologías emergentes como blockchain y la computación cuántica. Los resultados subrayaron la importancia de establecer normativas que garanticen el equilibrio entre innovación tecnológica y la protección de derechos humanos en un contexto de big data y decisiones automatizadas. Concluye enfatizando que el impacto de la IA trasciende lo técnico, consolidándola como motor de avance interdisciplinario, impulsando tanto el progreso del conocimiento humano como aplicaciones prácticas sostenibles, siempre bajo enfoques éticos y regulados.

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