Check out our work
A friendly, practical guide that lays out some best practices for creating useful, responsible AI applications.
Highly interactive, visual, and approachable explanations of key AI concepts.
Exploring ML ideas and issues, in non-technical features and conversations with diverse voices from around the world.
We build open-source tools to help make ML models more understandable, reliable, and fair.
Our research into computer science, HCI, and design focuses on making ML more understandable, trustworthy, reliably fair, and useful.
Podcast where a writer and a software engineer explore the human choices that shape machine learning systems by building competing tic-tac-toe agents.