"The key assumption is that the pattern of noise in the cause will be different to the pattern of noise in the effect. That’s because any noise in X can have an influence on Y but not vice versa."[...] "That’s a fascinating outcome. It means that statisticians have good reason to question the received wisdom that it is impossible to determine cause and effect from observational data alone." https://medium.com/the-physics-arxiv-blog/cause-and-effect-t...
Does not rule out shared cause. You observe X and Y and find a correlation. You still have to consider that X and Y are caused by Z. Noise in Z will have echoes in both X and Y.
I don't think it's hype or over stating things to suggest that this may be the most significant advance in practical statistics and methodologies for scientific investigation in years, perhaps decades.
Like many brilliant ideas, it seems so obvious in retrospect, another great "Why didn't I think of that?" moment.
Particularly since the confounding issue is really enormous in science. And sits at the core of the example the article gives in introduction... That would be an achievement in itself to build an experiment without confounder(s).
