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Buenas prácticas y límites de la IA.

Created by

daf flores
daf flores
Mexico

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IA Responsable: Verdadero o Falso
 

IA Responsable: Verdadero o FalsoOnline version

Buenas prácticas y límites de la IA.

by daf flores
1

Un modelo con alta precisión en un conjunto de pruebas siempre funcionará igual de bien en producción.

2

Se deben monitorizar continuamente los modelos para detectar deriva de datos.

3

La interpretación de modelos complejos no es necesaria si la puntuación de rendimiento es alta.

4

La IA debe entrenarse con datos representativos y diversificados.

5

Es correcto evaluar sesgos y equidad algorítmica en modelos de IA antes de su despliegue.

6

Es aceptable usar datos personales sin consentimiento para entrenar modelos si el rendimiento mejora.

7

La IA debe ser explicable cuando se toma decisiones críticas.

8

Es correcto desplegar IA para decisiones críticas sin plan de mitigación de riesgos ni pruebas piloto.

9

La IA debe entrenarse solo una vez y no necesita actualizaciones posteriores.

10

Se deben establecer límites de seguridad y privacidad para el uso de IA.

 
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