Feedback Loops for Continuous Bias Detection

Implementing feedback loops in which models are continually assessed and refined based on performance metrics related to bias can create an effective mechanism for ongoing bias detection. This approach acknowledges that bias detection is not a one-time task but requires constant vigilance. The effectiveness of feedback loops depends on the metrics used and the commitment to iteratively refine the models and data. Without these, there's a risk of perpetuating or even exacerbating existing biases.