Explainable AI refers to the ability to interpret model outcomes in a way that is easily understood by human beings. We explore why this matters, and discuss in detail tools that help shine light inside the AI "black box" -- we wish to not just understand feature importance at the population level, but to actually quantify feature importance on a per-outcome basis.
In a world overshadowed by the rapid deterioration of its climate, AI engineers are beginning to apply machine learning technology to issues of environmental justice and crisis. In California, where wildfires have ravaged over 570,000 acres of land and forced 41,000 evacuations already this summer, AI is being used to prevent and monitor forest fires throughout the state.
