Bias and Discrimination in Algorithms

Predictive analytics can inadvertently perpetuate existing biases present in historical hiring data, leading to discriminatory outcomes against certain demographic groups. To address this, organizations should audit algorithms regularly for bias, use diverse training datasets, and involve multidisciplinary teams—including ethicists and legal experts—in model development.