You’re completely correct about a couple of things, and not only am I not disputing them, they are crucial to my argument: first, that I am only focusing on only one side of the distribution, and the second, that the scenarios I am referring to (with WW2 counterfactual or nuclear war) are improbable.

Indeed, as I have said, even if the probability of the future scenarios I am positing is of the order of 0.00001 (which makes it improbable), that can hardly be the grounds to dismiss the argument in this context simply because longtermism appeals precisely to the immense consequences of events whose absolute probability is very low.

At the risk of quoting out of context:

If we increase the odds of survival at one of the

filters by one in a million, we can multiply one of the inputs forCby 1.000001.

So our new value ofCis 0.01 x 0.01 x 1.000001 = 0.0001000001

New expected time remaining for civilization =MxC= 10,000,010,000

In much the same way, it’s absolutely correct that I am referring to one side of the distribution ; however it is not because the other-side does not exist or is not relevant bur rather because I want to highlight the magnitude of uncertainty and how that expands with time.

It follows also that I am in no way disputing (and my argument is somewhat orthogonal to) the different counterfactuals for WW2 you’ve outlined.

This is a very interesting paper and while it covers a lot of ground that I have described in the introduction, the actual cubic growth model used has a number of limitations, perhaps the most significant of which is the assumption that it considers the causal effect of an intervention to diminish over time and converge towards some inevitable state: more precisely it assumes |P(St|A)−P(St|B)|→0 as t→∞, where St is some desirable future state and A and B are some distinct interventions at present.

Please correct me if I am wrong about this.

However, the introduction considers not just interventions fading out in terms of their ability to influence future events but often the sheer unpredictability of them. In fact, much like I did, the idea from chaos theory is cited:

But the model does not consider any of these cases.

In any case, by the author’s own analysis ( which is based on a

largenumber of assumptions), there are several scenarios where the outcome is not favorable to the longtermist.Again, interesting work, but this modeling framework is not very persuasive to begin with (regardless of which way the final results point to).