Note also that merely collecting Big Data would not have helped us ascend the ladder and answer the above questions. Assume that you are a reporter collecting records of execution scenes day after day. Your data will consist of two kinds of events: either all five variables are true, or all of them are false. There is no way that this kind of data, in the absence of an understanding of who listens to whom, will enable you (or any machine learning algorithm) to predict the results of persuading marksman A not to shoot.
This is an important point; to create a proper causal reasoning model, one needs to bring in extra information in order to know who does what; thus it becomes necessary, for instance, to know what tfs bind to what genes, and what tfs are able to interact with one another. This is an example of mind-first, or knowledge first, data second.
