Decades before today's deep learning neural networks compiled imponderable layers of statistics into working machines, researchers were trying to figure out how one explains statistical findings to a human.
IBM this week offered up the latest effort in that long quest to interpret, explain, and justify machine learning, a set of open-source programming resources it calls "AI 360 Explainability."