Removing gender-based and racial bias from the hiring process
As Product Owner for Gatello, while working with our design team on the interface I noticed our app had an in-built component that would allow for hiring bias to seep through the cracks. When employers reviewed recommended candidates previously, their personal data would be available. To counter this, I suggested the deployment of a gaussian blur and random string generation to aid in removing bias from the equation, or at least improve towards that common goal. Job seekers should be judged on merit, not identity.