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Lecciones de la ciencia de sistemas complejos para la gobernanza de la IA
Noam Kolt1,2, Michal Shur-Ofry1, Reuven Cohen3
1Faculty of Law, Hebrew University, Jerusalem, Israel.
Patterns (New York, N.Y.)
|August 22, 2025
Resumen
Los principios de los sistemas adaptativos complejos ofrecen ideas cruciales para gobernar la inteligencia artificial (IA). Aplicar estas lecciones ayuda a manejar la IA
Área de la Ciencia:
- Aplicaciones interdisciplinarias de la ciencia de los sistemas adaptativos complejos.
- Integración de ideas de la física, la biología y las ciencias sociales para la gobernanza de la IA.
- Aprovechar la teoría de sistemas complejos para comprender el comportamiento y los riesgos de la IA.
Sus antecedentes:
- Los sistemas contemporáneos de inteligencia artificial (IA) exhiben características de sistemas adaptativos complejos.
- Los entornos de IA muestran crecimiento no lineal, fenómenos emergentes y fallas en cascada.
- Los desafíos en la gobernanza de la IA se derivan de los circuitos de retroalimentación y las interdependencias de la infraestructura crítica.
Objetivo del estudio:
- Explorar la aplicabilidad de los principios de los sistemas adaptativos complejos a la gobernanza de la IA.
- Identificar los desafíos clave en la gobernanza de la IA iluminados por la ciencia de los sistemas complejos.
- Proponer un marco para la gobernanza de la IA compatible con la complejidad.
Principales métodos:
- Dibujando paralelismos entre los sistemas adaptativos complejos y el comportamiento de la IA.
- Analizar los desafíos de la gobernanza de la IA a través de la lente de los sistemas complejos.
- Examinar estudios de casos de salud pública y cambio climático para obtener información sobre la gobernanza.
Principales resultados:
- Los sistemas de IA y sus entornos comparten propiedades con sistemas adaptativos complejos.
- La profunda incertidumbre caracteriza los esfuerzos actuales para gobernar la IA.
- Las características específicas de la IA, como los bucles de retroalimentación de datos sintéticos, plantean desafíos de gobernanza.
Conclusiones:
- La gobernanza de la IA requiere principios compatibles con sistemas adaptativos complejos.
- Los datos deseados propuestos incluyen la intervención temprana/escalable, las instituciones adaptativas y los umbrales de riesgo calibrados.
- La gobernanza efectiva de la IA requiere estrategias adaptativas para gestionar la incertidumbre y los riesgos emergentes.
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