Earlier quoted context omitted.
A simple causal graph of "release -> observe drop" is not what Pearl is referring to when he talks about causality. He's talking about more complicated causal graphs where some hidden variables affected both the release and the fact that the vase was observed to drop, which can require careful experimental setup to figure out. "Release -> observe drop" with no other variables is something an associative model can lea…
Right — but it won’t learn those thousands of such rules, which in collection lead to “common sense” about the world, if it has no access to those, ie, if it’s disembodied.
AI is now "in the wild" though.