4 ms·
I don't see how that follows. Surely you could select hyper-parameters that cause a model to perform differently across different races, ethnicities, etc. Like,
by seoaeu 5y ago
I don't see how that follows. Surely you could select hyper-parameters that cause a model to perform differently across different races, ethnicities, etc. Like, shouldn't you be able to get a model to perform poorly for minority groups simply by specifying a model size that's too small to learn the full data set, with the knowledge that most training samples won't be describing those groups?
- djoldman 5y agoHrm, I think I understand what you're saying. Perhaps a better way to formulate it is: let's say we take a model and add a regularization term that penalizes/rewards some part of the data, which when trained makes for a morally/ethically biased model. I think you're exactly correct, the source of moral/ethical bias here is in the model. Good point.