FATE: Fairness, Accountability, Transparency, and Ethics in AI

We take a human-centered approach to transparency, empirically studying how to provide stakeholders of ML systems with the right information to achieve their goals.

The AI Fairness Checklist’s goal is to conduct an iterative co-design process with 48 AI practitioners across 12 technology companies to understand the role of checklists in AI ethics, focusing on fairness.​

Datasheets help dataset creators uncover sources of bias or hidden assumptions and help dataset consumers determine if a dataset meets their needs.