No I don't think I expressed myself clearly. The problem is that machine learning learns from biased data. The input data is the total US population, which has

No I don't think I expressed myself clearly. The problem is that machine learning learns from biased data. The input data is the total US population, which has wealthier groups than others. Because of the way we train machine learning (using all the data we have), the bias that is in the original data gets transfered to the logic. Specifically, a machine learning will produce different numbers for 2 individuals with the exact same characteristics except the race. And that is the problem that needs to be addressed. Let's put it in another context. Let's say I'm a white athlete, and I'm very good at running the 100m race. Actually I run just as fast as a black person who is my main rival. Now if someone has to select one of us to go to the Olympics, they should toss a coin to decide who goes. If you use a ML algorithm, it would absolutely send the black person, because no white people has won a 100m race in the last 20 olympics. That's the kind of bias ML does and that needs to be addressed.