Structural Causal Model and Explainable AI for Detecting Bias and Fairness in Automated Credit Decisions System
Fairness and bias concerns in AI systems arise when predictive models amplify inequities present in data, and measurement processes. Traditional fairness analysis approaches such as demographic parity, equalized odds, and individual fairness primarily operate on statistical associations and often struggle when protecte...