UnfairButFairML. In the field of fair machine learning, it is presumed that fair analyses should always omit, or at least reduce in influence, sensitive variables such as race and gender. But in some applications, those affected may actually want their sensitive traits to be used.

Problem

The full read on this project is a sign-in away — what it solves, who it serves, and where it sits in the market.

Audience

The full read on this project is a sign-in away — what it solves, who it serves, and where it sits in the market.

Market

The full read on this project is a sign-in away — what it solves, who it serves, and where it sits in the market.

Pricing

The full read on this project is a sign-in away — what it solves, who it serves, and where it sits in the market.