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Flujo de conocimiento de la ciencia a la tecnología de IA: Identificación de roles tecnológicos centrales y de
Seokhui Lee1, Jisoo Hur2, Junseok Hwang1
1Technology Management, Economics and Policy Program, College of Engineering/ Integrated Major in Smart City Global Convergence, Seoul National University, Seoul, Republic of Korea.
PloS one
|February 19, 2026
Resumen
Este estudio mapea el flujo de conocimiento de la ciencia a la tecnología en inteligencia artificial (IA). Analizamos patentes de IA para revelar tendencias clave y vías de innovación, ofreciendo información para I+D y políticas.
Área de la Ciencia:
- Inteligencia Artificial (IA)
- Estudios de Innovación
- Bibliometría
Sus antecedentes:
- La inteligencia artificial (IA) avanza rápidamente y se integra en todas las industrias.
- El flujo de conocimiento de la investigación científica al desarrollo tecnológico de la IA es crucial pero poco estudiado.
- La investigación existente carece de un análisis sistemático de las vías de conocimiento de la ciencia a la tecnología de la IA.
Objetivo del estudio:
- Investigar sistemáticamente el flujo de conocimiento de la ciencia a la tecnología que sustenta la evolución de la IA.
- Proponer y aplicar un marco semántico para explorar la transferencia de conocimiento relacionada con la IA.
- Identificar las tendencias tecnológicas clave y las vías estructurales en el desarrollo de la IA.
Principales métodos:
- Se desarrolló un marco de dos etapas: clasificación tecnológica y exploración de temas semánticos.
- Se clasificaron las patentes de IA utilizando medidas de centralidad de una red de coincurrencia de CPC.
- Se aplicó el modelado BERTopic a los resúmenes de patentes y publicaciones científicas, utilizando IA generativa para la etiquetación de temas.
Principales resultados:
- Se analizaron patentes de IA presentadas entre 2002 y 2021.
- Se rastrearon las tendencias tecnológicas clave y se identificaron las vías estructurales del flujo de conocimiento.
- Se reveló la interacción dinámica entre el descubrimiento científico y la innovación en IA.
Conclusiones:
- Los hallazgos proporcionan una comprensión estructural de la evolución tecnológica de la IA impulsada por el conocimiento científico.
- Ofrece implicaciones prácticas para las estrategias corporativas de investigación y desarrollo (I+D).
- Informa el diseño de políticas de innovación para el panorama en rápida evolución de la IA.
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