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Repensar la presentación de informes sobre los resultados de la evaluación en el ámbito de la IA
Ryan Burnell1, Wout Schellaert2, John Burden1,3
1Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge, UK.
Science (New York, N.Y.)
|April 13, 2023
Resumen
La comprensión de la investigación compleja se ve obstaculizada por las métricas agregadas y el acceso limitado a los resultados detallados. Esto limita el progreso científico y la transparencia de los datos.
Área de la Ciencia:
- Ciencia de los datos
- Metodología de la investigación
Sus antecedentes:
- Los informes de investigación actuales a menudo se basan en métricas agregadas.
- La falta de acceso a datos granulares impide una evaluación científica exhaustiva.
Objetivo del estudio:
- Para resaltar las limitaciones impuestas por las métricas agregadas.
- Abogar por un mejor acceso a los resultados de la investigación para una mejor comprensión.
Principales métodos:
- Análisis de las normas actuales de publicación científica.
- Revisión de las políticas de accesibilidad de los datos en la investigación.
Principales resultados:
- Las métricas agregadas ocultan detalles y variaciones cruciales dentro de los conjuntos de datos.
- El acceso restringido a los resultados en bruto o detallados limita la reproducibilidad y la evaluación crítica.
Conclusiones:
- La excesiva dependencia de las métricas agregadas dificulta el entendimiento científico.
- Facilitar el acceso a los resultados detallados de la investigación es esencial para el progreso científico.
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