Yes, but a holistic test requires a realistic counterfactual. That's the problem. There is no way to evaluate that counterfactual for a human interviewer. It i

Yes, but a holistic test requires a realistic counterfactual. That's the problem. There is no way to evaluate that counterfactual for a human interviewer. It is true that extreme bias/discrimination will be evident, but smaller bias/discrimination, particularly in an environment where the pool is small (say, black women for engineering roles) is extremely hard to prove for a human interviewer. Your sample size is just going to be too small. On the other hand, if you have an ML algorithm, you can feed it arbitrary amounts of synthetic data, and get precise loadings on protected attributes.