The Role of Artificial Intelligence in Data Science: Theoretical Perspectives and Emerging Challenges

• Autores: Reyes Risco, Anthony JeanPaul, De La Cruz Gamarra, Juan Aurelio, Torres Villanueva, Marcelino
• Formato: artículo
• Fecha de Publicación: 2025
• Institución: Universidad La Salle
• Repositorio: Revistas - Universidad La Salle
• Lenguaje: español
• OAI Identifier: oai:ojs.revistas.ulasalle.edu.pe:article/208
• Enlace del recurso: https://revistas.ulasalle.edu.pe/innosoft/article/view/208; https://doi.org/10.48168/innosoft.s23.a208; https://purl.org/42411/s23/a208; https://n2t.net/ark:/42411/s23/a208
• Nivel de acceso: acceso abierto
• Materia: AutoML; Big Data; Data Science; Algorithmic Ethics; Artificial Intelligence; Predictive Models; Ciencia de Datos; Ética algorítmica; Inteligencia Artificial; Modelos Predictivos

The article explored how Artificial Intelligence (AI) and Data Science have revolutionized the creation and analysis of information by integrating advanced methodologies that overcome traditional barriers in the interpretation of complex data. Fundamental concepts and current technical and ethical challenges were addressed, highlighting the automation of the analytical lifecycle through AutoML, the implementation of explainable models and the management of algorithmic biases. The research also examined the limitations of AI in processing unstructured data and its interaction with emerging technologies such as blockchain and quantum computing. The results highlighted the importance of establishing regulations that guarantee the balance between technological innovation and the protection of human rights in a context of big data and automated decisions. It concludes by emphasizing that the impact of AI transcends the technical, consolidating it as an engine of interdisciplinary progress, promoting both the progress of human knowledge and sustainable practical applications, always under ethical and regulated approaches.