No, my approach is asking all types of people about the experience of minority folks, including those minority folks (we are all minority folks in some aspect, even if this aspect is uninteresting).
> for instance, if you ask a statistically significant sample of the population about what it is like to be a trans man, you are going to (...) be asking a bunch of people who have no idea what it is like.
Then those people can answer that they don't know what it's like to be trans.
If somebody comes up to me and asks me: "what is it like to be trans?". My answer would obviously be: "how the hell should I know? I'm not trans".
But trans people can answer what it's like to be trans.
> And it gets worse. For instance, trans men have a totally different experience in rural vs coastal America vs Europe vs Africa. To get an AI who can speak confidently on what it is like to be trans male in those places will require even more interviews.
Yes, you can only spend a limited amount of effort towards the goal of being unbiased. The goal is to be as unbiased as possible given that limited amount of effort.
It's still better to make X amount of effort to be unbiased than zero effort.
This is also something that can be improved over time, as better ideas and methods become available regarding how to measure and decrease bias.
Perhaps even an AI can be used to detect these biases and reduce them as best possible.
> Now, you could say, "My AI simply will not speak about the experience of gay Black men, and the challenges/perspectives from that community", but then you've introduced a bias.
Or perhaps the AI can simply answer based on the information it was trained on, making a best guess as to what that would be like, taking into account all the data that was available to it and how that data was weighed to be as unbiased as possible.
> You could say, "Well, we'll go out and interview people from every set then, make sure we're covering everyone!"
No, I think you are making a significant mistake in this reasoning. There is no "every set". There is only one set. And that is the set of all people.
> But where then do you stop sampling? Each additional modifier adds exponential complexity -- gay Black men from New Orleans will have a different experience from gay Black men from Lagos.
What modifier? There is no modifier. "SELECT RANDOM(x%) FROM TABLE all_people" (or whatever the imaginary SQL syntax would be) :)