Hi Jeanne. Welcome to the EA Forum.

Are there other options that could stand human psychological biases, and practically cope with modern-time capacities (such as with the internet, complex interdependent global markets, etc.)?

I like libertarianism.

Thanks. That makes sense to me. Here is a brief explanation of fixed and random effects from Gemini.

Hi Ben. What are your current thoughts on this?

Hi Harri. Great post.

Thanks, Nicolas. I agree one should prioritise decreasing the uncertainty about changes in the population of nematodes, and in their welfare over doing whatever naively seems to increase their welfare the most cost-effectively based on current best guesses.

One thing that I find striking and that I think illustrates this point well: most of the explained variance in Li et al's models comes from data provider^[1] systematic effects, rather than from environmental or land-use variables. (See their supplementary info).

Which is the relevant table? I did not find "provider" in the Supplementary Information.

Hi Zwibel. Welcome to the EA Forum.

The post was written by Michael Huemer, not me. However, here is context about the quote you mentioned.

Hi Deena. Great post. I guess crossposting the whole post would have led to more engagement.

I see. Thanks for the patience. I could equally say that an intervention leads to a distribution for the future welfare whose minimum value W_min has probability p, and that inaction decreases it by 1 with probability 50 %, and increases it by 1 with probability 50 %, thus implying a minimum future welfare of W_min - 1 with probability 0.5*p. This is the exact opposite of what I concluded above, and suggests the lowest possible future welfare of W_min - 1 would be lower and more likely with inaction.

I agree both models are wrong. I cannot assume that the change in future welfare caused by the intervention is independent from the future welfare under inaction (as I did in my past comments), or that the change in future welfare caused by inaction is independent from the future welfare caused by the intervention (as I did just above).

Unless you believe the expected amount of wild animal suffering is higher all-things-considered than with inaction, you shouldn't really expect it to do worse according to "Avoiding the worst" risk aversion (as a heuristic; there could be exceptions).

I agree that increasing welfare in expectation is a good heuristic for better performance under "avoiding the worst" risk aversion. I have very little idea about whether cage-free campaigns for laying hens increase or decrease welfare in expectation. So I do not know whether they are favoured or not under "avoiding the worst" risk aversion. They are still disfavoured under difference-making and ambiguity risk aversion, and this could make them worse than inaction. In addition, they may be worse than inaction under no risk aversion of any type.

This looks a lot like the typical error people make for the original two envelopes problem.

The moral two envelopes problem is not problematic if there is a common scale to compare the welfare per unit time (as there is to compare temperature)?

Initial welfare (what does that mean?) and final welfare after inaction can differ, because the world, e.g. land use, will change even if you do nothing, and campaigns take time for their effects to materialize.

Suppose that inaction leads to a distribution for the future welfare (integral of the welfare per unit time across all future time) whose minimum value W_min has probability p. With an intervention that decreases future welfare by 1 with probability 50 %, and increases it by 1 with probability 50 %, the minimum future welfare would be W_min - 1 with probability 0.5*p. So I think the lowest possible future welfare of W_min - 1 would be lower and more likely with the intervention (although the intervention would not change future welfare in expectation).

If you swapped the roles of campaign and inaction

What do you mean by this? By definition, inaction does not change the distribution of the future welfare?

I think my point stands for any distribution describing the initial welfare. Imagine the minimum initial welfare W_min has probability p. With inaction, the minimum final welfare would still be W_min, and have probability p. With an intervention which decreases welfare by 1 with probability 50 %, and increases welfare by 1 with probability 50 %, the minimum final welfare would be W_min - 1 with probability 0.5*p. So the lowest possible welfare of W_min - 1 would be lower and more likely with the intervention?