Also known as: human in the loop (HITL) · HITL · Human in the Loop
HITL, o human-in-the-loop, es un enfoque en el que las personas siguen participando en la configuración, revisión, aprobación o mejora de salidas o decisiones de sistemas de IA. Se usa para combinar la eficiencia de la máquina con el juicio humano, especialmente en tareas de mayor riesgo o sensibles al contexto. HITL puede incluir supervisión, retroalimentación, validación, escalamiento o actividades de entrenamiento de modelos.
Human in the loop refers to the involvement of human oversight and decision-making in the processes that involve AI and automated systems. This approach allows for critical decisions, especially those impacting individuals, to be reviewed, verified, and influenced by human judgement and expertise.
A loosely-defined idiom that could mean either of the following: - A policy of viewing generative AI output critically or skeptically. - A strategy or system for ensuring that people help shape, evaluate, and refine a model's behavior. Keeping a human in the loop enables an AI to benefit from both machine intelligence and human intelligence. For example, a system in which an AI generates code which software engineers then review is a human-in-the-loop system.