You can fix the problem by going nuclear and omitting any sort of data that could serve as a proxy for the discriminatory signals, but it's possible to explicitly feed the discriminatory signals into the model and enforce that no combination of other data amounting to knowledge about them can influence the model's predictions.
There was a great paper floating around for a bit about how you could actually manage that as a data augmentation step for broad classes of models (constructing a new data set which removed implicit biases assuming certain mild constraints on the model being trained on it). I'm having a bit of trouble finding the original while on mobile, but they described the problem as equivalent to "database reconstruction" in case that helps narrow down your search.
People have a limited tolerance. Then they start telling you to take care of yourself and strongly encouraging you to leave.
It’s why I switched to remote work before the pandemic. If a bad episode starts up I can cover for it much more easily.
I wonder if the answer to the disability question is something the AI uses when evaluating candidates, and if it has learned to just toss out anyone who says yes?
High School: Florida School for the Deaf and the Blind.
Other Experience: President of Yale Disability Awareness Club (2009-2011).