[self-censored to prevent further downvotes because HN is downvoting me for what I said and the delete button is gone; sorry it seems discussion about solutions to racial issues isn't welcome here]
Oddly it seems like you are the person who doesn't want to have a discussion.
You stated "As an ML engineer I can tell you confidently here's how you fix these systems" and people critiqued your solution. Is that not being open to discussion?
Because presumably, if it works like many other systems, if you get downvoted enough, you probably get banned, so it means I should be scared to say what I said again.
If people were interested in debating like mature adults without downvoting then I would have left it up and continued the discussion.
You need your consumer base to be represented in your product development system. In training an AI model we first test things with what we are personally have a bias for.
For example in training a stock prediction model, I am going to first test it with the most familiar stocks that I know or I have bias for. And I am going to adjust my model until I find the model being correct for my bias then test it across a larger dataset.
I don't work in AI but I know that test data is incredibly large and they supposedly systematically cover all bases. But what I am saying is this the chance of random events will go down when you deviate from a homogenous development team where everyone is biased towards the same things because they share cultural and racial overlaps.
This is not the real motivation for diversity initiatives since otherwise you would see a push to hire more old Republicans.