Statistics versus Machine Learning: should they really be opposed?

This "seemingly" old debate deserves to be revisited with fresh perspective. Even though the field of application is fairly recent, the basic methods used in Data Science are for the most part some forty years old now. To recall, the two main branches concerned are statistics on the one hand, and machine learning on the other, to which I would add a third branch that consists of what could be called "business ontologies" i.e. "structured sets of terms and concepts representing business know-how or a field of application" (Wikipedia). We can notice that some people are absorbed by the versus debate, comparing the statistical and machine learning approaches, and their efficiency, ROI and cost within the context of predictive applications (predictive marketing, Digital Marketing, customer knowledge, etc.). This debate is by no means a new one in the sense that the two "schools" sprang from two different intellectual trends.