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Una taxonomía de riesgos y herramienta de reflexión para la adopción de modelos de lenguaje grandes en salud pública

Jiawei Zhou¹, Amy Z Chen¹, Darshi Shah¹

¹Georgia Institute of Technology, Atlanta, GA, United States.

Proceedings of the ACM on human-computer interaction

|February 20, 2026

Resumen

Los modelos de lenguaje grandes (LLM) presentan riesgos en salud pública. Este estudio introduce una taxonomía de riesgos para ayudar a los profesionales a evaluar la adopción de LLM y mitigar los daños potenciales en diversos contextos de salud.

Área de la Ciencia:

Salud Pública
Inteligencia Artificial
Comunicación de Salud

Sus antecedentes:

Los modelos de lenguaje grandes (LLM) ofrecen potencial pero generan preocupaciones para la difusión de información de salud pública.
Los marcos de evaluación de riesgos existentes para LLM son insuficientes para el dominio de la salud pública de alto riesgo.

Objetivo del estudio:

Explorar las preocupaciones sobre la adopción de LLM en salud pública.
Desarrollar una taxonomía de riesgos para evaluar el uso de LLM en áreas críticas de salud pública.

Principales métodos:

Se realizaron grupos focales con profesionales de la salud pública y personas con experiencia vivida.
Se examinaron las preocupaciones en la prevención de enfermedades infecciosas, el trastorno por uso de opioides y la violencia de pareja íntima.

Principales resultados:

Desarrolló una taxonomía de riesgos con cuatro dimensiones: individual, atención centrada en el ser humano, ecosistemas de información y rendición de cuentas de la tecnología.
Identificó riesgos específicos y proporcionó preguntas de reflexión para los profesionales.

Conclusiones:

La adopción de LLM en salud pública requiere un enfoque reflexivo sobre los riesgos.
Se necesita un vocabulario compartido y una herramienta de reflexión para la evaluación colaborativa de riesgos y la mitigación de daños.
Enfatiza la importancia de la experiencia vivida y la experiencia en el dominio para evaluar las aplicaciones de LLM.

Palabras clave:

IA generativa necesidad de información de salud tecnologías de la información y la comunicación búsqueda y apoyo de información modelos de lenguaje grandes salud pública taxonomía de riesgos

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