As previously stated, the take on causality’s math is meant to be academically standard; this includes the idea of decomposing the X(i) into deterministic F(i) and uncorrelated U(i).
I haven’t particularly seen anyone else observe that claiming you know about X without X affecting you, you affecting X, or X and your belief having a common cause, violates the Markov condition on causal graphs.
I haven’t actually seen anyone cite the Markov condition as a reply to the old “What constitutes randomization?” debates I’ve glimpsed, but I would be genuinely surprised if Pearl & co. hadn’t pointed it out by now—my understanding is that he’s spending most of his time evangelizing causality to experimental statisticians these days. It seems pretty obvious once you have causal models as a background.
The concept of “separate magisteria” is as old as scientific critique of religion, but the actual phrase was coined by Stephen Jay Gould (speaking favorably of the separation, natch). So far as I know, the concept of anti-epistemology is an LW original; likewise the view that causality is more general than anyone trying to separate their magisterium would have the mathematical competence to successfully escape, even as an attempted excuse. In general, when I write about the skeptical applications, I’m usually writing things I haven’t read before and that wouldn’t be expected to appear somewhere like Pearl’s Causality book—which doesn’t imply that nobody else has written about them, of course. If you know of similar theses, comment here.
I haven’t actually seen anyone cite the Markov condition as a reply to the old “What constitutes randomization?” debates I’ve glimpsed
Isn’t this essentially implied by the well-known ideas of “natural experiments” and “instrumental variables”? Pearl does deal with these ideas in Causality.
Mainstream status:
As previously stated, the take on causality’s math is meant to be academically standard; this includes the idea of decomposing the X(i) into deterministic F(i) and uncorrelated U(i).
I haven’t particularly seen anyone else observe that claiming you know about X without X affecting you, you affecting X, or X and your belief having a common cause, violates the Markov condition on causal graphs.
I haven’t actually seen anyone cite the Markov condition as a reply to the old “What constitutes randomization?” debates I’ve glimpsed, but I would be genuinely surprised if Pearl & co. hadn’t pointed it out by now—my understanding is that he’s spending most of his time evangelizing causality to experimental statisticians these days. It seems pretty obvious once you have causal models as a background.
The concept of “separate magisteria” is as old as scientific critique of religion, but the actual phrase was coined by Stephen Jay Gould (speaking favorably of the separation, natch). So far as I know, the concept of anti-epistemology is an LW original; likewise the view that causality is more general than anyone trying to separate their magisterium would have the mathematical competence to successfully escape, even as an attempted excuse. In general, when I write about the skeptical applications, I’m usually writing things I haven’t read before and that wouldn’t be expected to appear somewhere like Pearl’s Causality book—which doesn’t imply that nobody else has written about them, of course. If you know of similar theses, comment here.
Isn’t this essentially implied by the well-known ideas of “natural experiments” and “instrumental variables”? Pearl does deal with these ideas in Causality.