Why&How: Interpretable ML

Explanation of classification ‘tabby’ as produced by LRP. Photo by author, heatmap implementation available at https://lrpserver.hhi.fraunhofer.de/image-classification.

Interpretable Machine Learning (or interpretable AI) techniques got a lot of attention recently as an attempt to open the black box of modern predictive algorithms (mostly neural nets). And it is not just in academia, policymakers and businesses as well have realized that interpretability is a key to warding off potential dangers arising from the notoriously instable ML models being deployed in businesses, public health, criminal justice, and…