Breiman's 'Two Cultures' Revisited and Reconciled

In a landmark paper published in 2001, Leo Breiman described the tense standoff between two cultures of data modeling: parametric statistical and algorithmic machine learning. The cultural division between these two statistical learning frameworks has been growing at a steady pace in recent years. What is the way forward? It has become blatantly obvious that this widening gap between "the two cultures" cannot be averted unless we find a way to blend them into a coherent whole. This article presents a solution by establishing a link between the two cultures. Through examples, we describe the challenges and potential gains of this new integrated statistical thinking.
Comment: This paper celebrates the 70th anniversary of Statistical Machine Learning--- how far we've come, and how far we have to go. Keywords: Integrated statistical learning theory, Exploratory machine learning, Uncertainty prediction machine, ML-powered modern applied statistics, Information theory