What is Bias Detection & Fairness Testing?

Bias Detection and Fairness Testing are techniques used to identify systematic favouritism or discrimination in AI model outputs. Testing covers protected attributes including race, gender, age, and socioeconomic status. Fairness metrics quantify disparities and inform remediation before deployment.

With POPIA, NDPA, and other African data protection laws emphasising fairness and non-discrimination, bias testing is becoming a regulatory expectation rather than an optional practice. Enterprises deploying AI in credit, hiring, or insurance must demonstrate that their models treat all groups equitably.