> The method, in the form of an algorithm, takes in data that have been collected over time, such as the changing populations of different species in a marine environment. From those data, the method measures the interactions between every variable in a system and estimates the degree to which a change in one variable (say, the number of sardines in a region over time) can predict the state of another (such as the population of anchovy in the same region).
I also read the introduction of the paper. Maybe I misunderstood something about causal inference, but I thought from data alone one could only infer correlations or associations (in general). To talk about "causal" links, I thought you need either to assume a particular model of the data generation process, or perform some interventions on the system to be able to decide the direction of the arrows in the "links" in general.
I'm not saying that the paper is wrong or anything, it looks super useful! It's just that one should be careful when writing/reading the word "causal".