How data is changing the classical way of scientific theorisation

These are the very measures that have long differentiated scientific activities from non-science. Moreover, scientists have been trained to differentiate between correlation and causation, that one must find a cause-effect relationship to understand and accept a correlation. But with the advent of humungous data, machine learning and black-box models, we are shifting to mere correlations. The shift in approach was predicted by Chris Anderson more than a decade ago, asserting that at the petabyte scale, information is about dimensionally agnostic statistics that requires us to forego the visualisation of data. For science that has always been about causation, the new change pushes it to the considerations of correlations.