Similarly, I would guess random changes are more likely to reduce population sizes than increase them (in the short term) because animals are somewhat finely tuned for their specific conditions, and if it’s the case that animal welfare is on average bad in the wild, then the expected decrease in average welfare would be made up for by a large enough reduction in the number of animals. If average welfare is positive or 0, then a random change seems bad in expectation.
In the long term, we need to compare equilibria, and I don’t have any reason to believe a random change leads to worse equilibria in expectation. EDIT: Sufficiently uncorrelated random changes (especially mutations) across individuals/populations provide variation that evolution can use to find better solutions. I have clulessness about a random change to a given population: it can drive it to extinction, or drive it in the direction towards greater intelligence and eventually colonizing space.
This means is that if we’re sufficiently confident that the short-term effects of a given intervention are good (and ignore the effects of the fact that we’re doing anything at all, e.g. effects on the movement, moral circle expansion), then without knowing more about the specifics of the intervention, we don’t have an overall reason to favour the status quo over the new equilibrium it would reach, other than possibly the costs to implement it. If it’s cost-effective in the short term and a wash in the long term, then it seems worth doing.
If we know enough about the specifics of the intervention, though, we can break symmetry or get stuck with complex cluelessness, and this seems likely to actually happen. But things could balance out through diversification with sufficiently many different such interventions that are cost-effective in the short term*, or by using some kind of careful hedging against potentially negative long term effects.
Similarly, I would guess random changes are more likely to reduce population sizes than increase them (in the short term) because animals are somewhat finely tuned for their specific conditions, and if it’s the case that animal welfare is on average bad in the wild, then the expected decrease in average welfare would be made up for by a large enough reduction in the number of animals. If average welfare is positive or 0, then a random change seems bad in expectation.
In the long term, we need to compare equilibria, and I don’t have any reason to believe a random change leads to worse equilibria in expectation. EDIT: Sufficiently uncorrelated random changes (especially mutations) across individuals/populations provide variation that evolution can use to find better solutions. I have clulessness about a random change to a given population: it can drive it to extinction, or drive it in the direction towards greater intelligence and eventually colonizing space.
This means is that if we’re sufficiently confident that the short-term effects of a given intervention are good (and ignore the effects of the fact that we’re doing anything at all, e.g. effects on the movement, moral circle expansion), then without knowing more about the specifics of the intervention, we don’t have an overall reason to favour the status quo over the new equilibrium it would reach, other than possibly the costs to implement it. If it’s cost-effective in the short term and a wash in the long term, then it seems worth doing.
If we know enough about the specifics of the intervention, though, we can break symmetry or get stuck with complex cluelessness, and this seems likely to actually happen. But things could balance out through diversification with sufficiently many different such interventions that are cost-effective in the short term*, or by using some kind of careful hedging against potentially negative long term effects.
* And at any rate, “doing nothing” would be only one among the many interventions we could diversify across, and under some assumptions with high model ambiguity, would only make up a small part of the optimal portfolio.