Can a Model Be Differentially Private and Fair?
Training models with differential privacy stops models from inadvertently leaking sensitive data, but there's an unexpected side-effect: reduced accuracy on underrepresented subgroups.
Can a Model Be Differentially Private and Fair? Explorables Can a Model Be Differentially Private and Fair? Training models with differential privacy stops models from inadvertently leaking sensitive data, but there's an unexpected side-effect: reduced accuracy on underrepresented subgroups. Imagine you want to use machine learning to suggest new bands to listen to. You could do this by having lots of people list their favorite bands and using them to train a model. The trained model might be quite useful and fun, but if someone pokes and prods at the model in just the right way, they could ex
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