Revisión sistemática de taxonomías de riesgos asociados a la Inteligencia Artificial
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Este artículo realiza una revisión sistemática de treinta y seis taxonomías de riesgos asociados a la Inteligencia Artificial (IA) que se han realizado desde el 2010 hasta la fecha, utilizando como metodología el protocolo Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). El estudio se basa en la importancia de estas para estructurar la investigación de los riesgos y para distinguir y definir amenazas. Ello permite identificar las cuestiones que generan mayor preocupación y, por lo tanto, requieren mejor gobernanza. La investigación permite extraer tres conclusiones. En primer lugar, se observa que la mayoría de los estudios se centran en amenazas como la privacidad y la desinformación, posiblemente debido a su concreción y evidencia empírica existente. Por el contrario, amenazas como los ciberataques y el desarrollo de tecnologías estratégicas son menos citadas, a pesar de su creciente relevancia. En segundo lugar, encontramos que los artículos enfocados en el origen del riesgo tienden a considerar más frecuentemente riesgos extremos en comparación con los trabajos que abordan las consecuencias. Esto sugiere que la literatura ha sabido identificar las potenciales causas de una catástrofe, pero no las formas concretas en las que esta se puede materializar en la práctica. Finalmente, existe una cierta división entre aquellos artículos que tratan daños tangibles presentes y aquellos que cubren daños potenciales futuros. No obstante, varias amenazas se tratan en la mayoría de los artículos de todo el espectro indicando que existen puntos de unión entre clústeres.
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