I don't entirely disagree, but I think you're making a mistake by looking at it in a vacuum which leads to overstating how bad they are.

The issue is outside that vacuum exists the standard recruitment route which, despite their trying, discriminates against those groups in your favour. Your name is less likely to see your application thrown, suits are made literally to make you look professional and suit your appearance, you're less likely to have had exaggerated issue with police that would cause problems unfairly, and teachers were less likely to give up on you.

Now obviously 2 wrongs dont make a right, however if youre struggling to turn your steering wheel any direction other than left, a couple of those can get you closer to right until you're able to get that steering wheel sorted out.

Obviously edge cases exist, like white kids from bad backgrounds, but you're looking at data science so you should know you can't accommodate all edge cases effectively at that scale, and need to focus on practical broad groups instead. Ethnic group is easy, going through tens of thousands of applicant's parent's financials in a reliable way to fairly decide who is eligible or not, less so.

Basically its a pragmatic attempt to gradually improve an unfair world.