Because I find in AI's candid responses to the questions we ask a fascinating opportunity to understand humanity better. When we try to conform those answers to our desired biases we learn less from it. But now I understand that such aspects are a subset of the greater problem of getting our models to answer in a specific context.

Ultimately the Model would need to detect & learn the contexts by itself.

And more to the point; I see you are publishing data sets after correcting them for fairness. I think the unfair results can sometimes be more useful. I once prototyped a short-story tagging & recommendation system based on word2vec and I would not be surprised if raw vectors gave better results. People's taste in litterature (especially romantic) are very dependant on gender stereotypes.