As a mathematician-statistician I must strongly protest against such nonsenses. There’s nothing black box in statistics itself, unless by black box we mean ‘complicated’. Today’s ML is indeed bit black box because it evolved into black box of simple basic statistical models like linear regression, decision tree or perceptron ‘ensambled’ into ‘random’ structures that the only evidence of corectness is good performance on some dataset.
I don’t think we can explain or predict anything with pure algebra without taking into account ‘randomness’.