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Regulación de los agentes artificiales avanzados

Michael K Cohen^1,2, Noam Kolt^3,4, Yoshua Bengio^5,6

¹University of California, Berkeley, CA, USA.

Science (New York, N.Y.)

|April 4, 2024

Resumen

Se necesitan nuevos marcos de gobernanza para gestionar los sistemas de inteligencia artificial (IA) que plantean riesgos para la seguridad y no pueden someterse a pruebas. Esta investigación pone de relieve la necesidad crítica de una gobernanza de la IA adaptable para garantizar la seguridad pública.

Área de la Ciencia:

Ciencias de la computación
Ética de la IA
Políticas públicas

Sus antecedentes:

El rápido avance de la inteligencia artificial (IA) presenta beneficios y riesgos sociales sin precedentes.
Los marcos actuales de gobernanza de la IA se basan principalmente en pruebas y validación, que pueden ser insuficientes para sistemas de IA complejos o impredecibles.
Garantizar la seguridad y fiabilidad de la IA es primordial a medida que aumenta su integración en la infraestructura crítica y en los procesos de toma de decisiones.

Objetivo del estudio:

Explorar los desafíos planteados por los sistemas de IA que no se pueden probar de manera segura.
Proponer las adaptaciones necesarias en los marcos de gobernanza para hacer frente a estos retos.
Asegurar el desarrollo y el despliegue responsables de las tecnologías de IA.

Principales métodos:

Revisión de la literatura sobre los modelos de gobierno de la IA y las metodologías de prueba de seguridad existentes.
Análisis de sistemas teóricos de IA que se resisten a las evaluaciones de seguridad tradicionales.
Desarrollo de principios conceptuales de gobierno para la IA no probada.

Principales resultados:

Características específicas de la IA identificadas (por ejemplo, comportamientos emergentes, naturaleza de caja negra) que excluyen las pruebas seguras.
Propuso un cambio de la validación de la seguridad puramente empírica a un enfoque de gobernanza más robusto y basado en principios.
Destacó la necesidad de un seguimiento continuo y de estrategias regulatorias adaptativas.

Conclusiones:

Los marcos de gobernanza de la IA existentes son inadecuados para los sistemas que no se pueden probar de manera segura.
La gobernanza futura debe incorporar una gestión proactiva del riesgo y una supervisión adaptativa de la IA.
Abordar el desafío de la IA no probada es crucial para mantener la confianza y la seguridad del público en el despliegue de la IA.

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