I second this but not for the conventional reasons of diversity but the subtleties diversity could be difficult to understand. You need your consumer base to b

I second this but not for the conventional reasons of diversity but the subtleties diversity could be difficult to understand. 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.