What you're asking is for it not just to be unbiased, but to correct for the fact that the real world is biased.

For example even though the data accurately shows that most CEOs are white men, we think this is a flaw in the world and we'd like to change it. This means the model has to have an understanding not just about the world, but about our goals for racial equality.

Now, I don't think this is as impossible as it might sound! LLMs are starting to get large enough to understand such complex ideas, and you can get large models to produce more representative outputs simply by asking them to be unbiased. It's an active research area.