Deuda Técnica en el Desarrollo de Software habilitado por la IA y su impacto sociotécnico: una revisión sistemática de la literatura
Resumen
Los conjuntos de herramientas de Inteligencia Artificial (IA) están siendo utilizados para desarrollar software innovador con gran rapidez, aunque seguir estos atajos podría generar Deuda Técnica de la IA (DTIA). Este tipo de deuda puede tener consecuencias tanto en lo técnico, como en lo social. Sin embargo, los desarrolladores no siempre son conscientes de si están incurriendo en DTIA durante sus proyectos. Peor aún, desconocen sus impactos sociotécnicos y cómo mitigarlos. Para reducir esta brecha, se desarrolló una Revisión Sistemática de la Literatura (RSL) para averiguar cuáles son los tipos y prácticas de DTIA, así como cuáles son sus repercusiones sociotécnicas. Los resultados arrojaron variedad de tipos y antipatrones de DTIA, así como prácticas para identificarla y mitigarla. También, se encontró que existen daños a la calidad, seguridad y mantenibilidad del producto, además de retos como sesgos y discriminaciones. Esta información puede apoyar a científicos y practicantes para detectar y gestionar la deuda técnica y social en contextos de desarrollo de software habilitado por la IA.
Citas
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