CertScroll

Bias and fairness

Systematic skew in a model's outputs that tracks a protected or sensitive attribute, inherited from training data, from the people who labeled it, or from which use cases got tested before launch. An aggregate accuracy score can hide a large gap between subgroups, which is why fairness evaluation is reported per group, not as one number.