Example Concept: Developers should incorporate bias detection tools and fairness metrics early in the design process to identify potential biases in training data and model outputs. Techniques such as re-weighting, data augmentation, and adversarial debiasing can be used to mitigate bias. Regular audits and updates to the model based on fairness assessments are also essential to maintain ethical standards.