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:
.… we knowon theoretical grounds that complex systems can be extremely sensitive to initialconditions, such that very small changes produce very large differences in later con-ditions (Lorenz, 1963; Schuster and Just, 2006). If human societies exhibit this sortof “chaotic” behavior with respect to features that determine the long-term effectsof our actions (to put it very roughly), then attempts to predictably influence thefar future may be insuperably stymied by our inability to measure the present stateof the world with arbitrary precision.
But the model does not consider any of these cases.
In any case, by the author’s own analysis ( which is based on a large number 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).