No there are ways to establish causation separate from correlation.
It's easy. Imagine, you observe someone with his hand on a switch. Every time he flips the switch the light turns on or off. This is correlative. You observe a correlation between switch flipping and lights going on and off. You can guess that the switch "causes" the light to go on.
However correlations do not indicate causation. It could be the switch doesn't do anything. The person is simply observing when the light goes on flipping the switch at the same time.
To do a causative experiment you have to become the flip switcher yourself. You have to randomly flip the switch and observe the lights reaction when it is flipped and when it is not flipped. Doing this more and more yourself as the experimenter gives you more and more confidence that the switch is causative to the light going on.
Essentially that is what a causative experiment requires. The experimenter must intervene with the subject itself in order to determine causation. Observational experiments are not enough to determine causation.
Judea pearl gets into this deeper with counterfactuals which actually imo is more technically correct but makes the whole thing harder to understand.
Anyway if you look at clinical trials this is exactly what they do to see if a certain medicine "causes" something.
Keep in mind that correlation and causation is sort of separate from the fact that science can't "prove" anything. Correlation is simply a probabilistic number and so is causation. Proof is something outside of this that exists in mathematics and logic.
> So why we need AI to understand causation when even we don’t have it.
We have causation. For example, it is impossible to communicate ideas, for example, without resorting to clear distinction of cause and effect. "To turn lights on press a button." It implies causation: pressing a button causes lights to turn on. It is impossible to express with correlation only.
> It’s correlation all the way down.
It is a reductionism. Like atoms have no life in them, therefore there is no life.
> We should strive for truth but know that we will never achieve any
It depends... We can know some Truths already, the trouble is we have no way to distinguish them from mere truths, which are just waiting for a counter example. In this sense we either achieved Truth already, or at least have a good chance to achieve it in a future.
> that is only one counter example from disproving entire theories.
Good theories cannot be disproved. Newton's gravitation is an example of this: it seems impossible to disprove. It has known applicability limits and it just works within them. I do not believe it will be disproved in a future. Or Euclid geometry on a plane as a different example.
Yeah, I can. And you can also. You can try this button yourself. You can ask others. You can try to get light-bulb off, and to repeat all other your experiments. You can bring another button and see how people would act. Any kid can find this causal link and identify it as a causal. Scientists was unable to do it with statistics because they rejected too much. But it tells us about weak reasoning abilities of a science, not about non-existence of cause and effect. Now this era of a weak reasoning is coming to an end, because now we have a math of causation.
The closest thing we have to “causation” is the scientific method and even that is only one counter example from disproving entire theories.
So why we need AI to understand causation when even we don’t have it.
It’s correlation all the way down. We should strive for truth but know that we will never achieve any