Comment by ordu
> The solution should not be to change the data but educate that group to change their behavior.
1. This is easier to say than to do.
2. In reality what you see is a correlation. If you try to educate all 20 year old females to not become a connected to organized crime CEOs of construction companies, your efforts will be wasted with 99% of these people, because they are either not connected to organized crime or are not going to become CEOs. Moreover the very your efforts will lead to a discrimination of 20 years old females, if not due to public perception of them, then because you've just increased difficulties for them of becoming a CEO.
> The goal is to identify and flag fraud cases.
Not quite. The goal is to reduce the amount of fraud cases. To identify and flag is a method of achieving that goal. But policymakers has a lot of other goals, like avoiding discrimination or reducing rate of murders. By focusing on one goal policymakers might undermine other goals.
As a side (almost methaphisical) note: it is one of the reason, why techies are bad at social problems. Their math education taught them to ignore all irrelevant details, when dealing with a problem, but society is a big complex system where everything is connected, so in general you can't ignore anything, because everything is relevant. But education have the upper hand, so techies tend to throw away as much complexity as it is needed to make the problem solvable. They will never accept that they don't know how to solve a problem.
"your efforts will lead to a discrimination of 20 years old females"
I'd think that this is an extremely far-fetched example that fails at basic logic. Just because a very specific scenario will be flagged does not mean that this scenario is generalized to all CEOs, all females, all 20 year olds.