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Regulación de los agentes artificiales avanzados

Michael K Cohen1,2, Noam Kolt3,4, Yoshua Bengio5,6

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Resumen
Este resumen es generado por máquina.

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.

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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.