I think I see now, thanks for the clarification. We don’t currently include funds/interventions that specifically work on research (to reduce key uncertainties or otherwise). We do think this kind of work is important, and we aim to include more topics (which could include “meta” work and research) in future iterations of the model. 

Hi Vasco,

Thanks for the question! We've designed the Donor Compass to be more streamlined, but we certainly appreciate and share your moral uncertainty. Our recommendations for the Cross-Cause Fund take into consideration 14 distinct worldviews, which take into account a wide range of animal moral weights (among other variables). You can investigate the assumptions for each here, along with the credences placed on each. If the range of views you place credence on significantly differ, however, you can use the Advanced Mode of the Cross-Cause fund to tailor it to your specific needs. (The definitions of each term can be found in this spreadsheet) 

Hi Benton,

Thanks for the comment! To clarify, our model and recommendations do draw upon the same approaches to moral uncertainty as our moral parliament. Our Cross-Cause Fund draws upon 14 different worldviews (see here for the exact details) and uses a weighted average of recommendations across nine methods of aggregating across them. 

Additionally, though our main Donor Compass tool is simplified, you can use a more Advanced Mode here to incorporate moral uncertainty across several combinations of worldviews. (I’m not familiar with Ross’ prima facie duties theory, but hopefully you could represent it adequately in the model.) Then, just like the Moral Parliament, you can specify which aggregation method you want to apply to resolve disagreements between worldviews. 

Of course! We're also happy to answer any additional methodological questions you may have in the future

Hi Clara, 

Thanks for the good question! 

Short answer: yes, you're understanding this correctly. And, yes, the model's allocations can be sensitive to putting any non-zero weight in for the value of impacts 500+ years out (but worldview diversification can mitigate this factor's impact on the outcome).

The model computes a "score" for each fund based on the sum of: (impact in time period t)*(weight in time period t) over all time periods. 

In our estimates of the impacts of GCR funds, we do take the approach of estimating the impact of avoiding an existential catastrophe over many generations in the future. As such, if you were to give full weight to further-out time periods, the vast majority of the expected impact of avoiding an existential catastrophe is in the long-run future. So any weight that is meaningfully above zero will make these projects have a large-in-magnitude score, all else equal, compared to putting a weight of zero. (We're preparing a more detailed sensitivity analysis that we'll release soon, and which will address your question in more detail.) 

Nevertheless, it's important to note that our recommended allocations are influenced by 14 worldviews, some of which assign zero weight to the far future. As such, we're not forced to choose between putting zero weight on the 500+ year period vs. some non-trivial amount that swamps the calculations. This creates a meaningful amount of diversification within the model's results, allowing other factors like moral weights to be influential. 

Additionally, there's an interaction between risk attitudes and the amount of weight that one puts on the far future, such that putting a non-zero amount on the 500+ year period doesn't automatically recommend you spend 100% of your budget on GCR funds. For instance, if you're highly risk-averse and put a weight of 1% on the 500+ year period, then you might avoid funding certain GCR funds that have a high enough chance of raising existential risk, because permanently harming the long-run future would have such a considerable impact. 

If you're interested in reading more about the worldviews we've used in the model, please feel free to reference this link. 

Thanks again for the question!

Beautifully written, and thanks for your work!

Hi Vasco,

When Bob was selecting the species, he was thinking of adult insects as the edge cases for the model (bees, BSF). He included juveniles to see what the model implies, not because he really thought the model should be extended to them. You'll notice that, in the book, the species list narrows considerably partly for this reason.

On the points related to sentience-conditioned welfare ranges, e.g. "So an organism having 0 neurons only decreases its welfare range conditional on sentience, and the rate of subjective experience of humans by 1/9. I understand having no neurons at all would also lead to a lower probability of sentience, but I think it should directly imply a much larger decrease in the welfare range conditional on sentience."
I think it's a mistake to point to a hypothetical sentience-conditioned welfare range, which is an intermediate step in the calculations, for an animal that has zero neurons as indicative of an issue with the methodology overall for animals with complex brains. 

Put straightforwardly, if an animal has zero neurons, it would have a welfare range of 0 overall, because I would give it a zero percent chance of being sentient, which affects all the models.

I also am not going to put a precise probability of sentience on nematodes, but I do think it's much much closer to zero and crosses the threshold of being Pascal's mugged.

I'm finding these discussions very draining and not productive at this point, so will not be engaging further in this debate. 

Hi Vasco, 

I just want to make a few points: 

1. We didn’t do the welfare range calculations for plants, protists, nematodes, etc, because we don’t think the methodology is appropriate for organisms that lack a complex brain and/or nervous system. There are a lot of methodological complexities with even applying them to complex farmed animals like chickens, and if we were to try to do something similar for very simple organisms, we might take a quite different approach.
2. We don’t really put much stock in the probability of sentience estimates, which weren't the focus of the project and are subject to much more uncertainty than the welfare range estimates themselves conditional on sentience (which themselves are highly uncertain). If you read the welfare range report’s footnotes, you’ll find that the 6.8% probability of sentience estimate for c elegans is driven substantially by my interpretation there that “probably not sentient” meant 10-35%, which was really just an off-the-cuff judgment. The other people whose views were included in that assessment gave under 1% or under 2% probabilities of sentience, and updating based on the proxies didn’t budge the priors much. On reflection, I think lower numbers are more appropriate than 6.8%, and I really would not anchor on that as “RP’s own lights”. 
3. I think part of this stems from a misunderstanding about the spreadsheets that I mistakenly linked to in the welfare range report. The vast majority of the calculations in the spreadsheet you were working off of were from a very early draft of the project, before we had ironed out a methodology and which animals we thought the methodology could apply to. Since they were a first draft and lack the full context of decisions we made along the way, I really would not consider them as our official position. I am sorry for any confusion that may have caused with respect to our methodology, opinions, or the scope of the project. Here are updated tables containing the proxies: Public Welfare Range Data and Public sentience table (Though, please note that the sentience proxies do very little work at all in the sentience probability assessments, which, again, we don’t put that much stock in, particularly for simple animals)
4. On the 0.00027 welfare range being high: 1) this was just an example to illustrate that Nick isn't correct about the structure of the model guaranteeing high numbers, not to show that it's a suitable welfare range estimate for nematodes per se. We’re not claiming that it’s actually what we would arrive at if we did assess nematodes under a more appropriate framework. And 2) it’s only high if you think you can multiply very small numbers by very big numbers and then act on that, which is a separate point. 
5. I think it’s fine if you or others have a different approach to weighing lean/likely no proxies, that was a judgment call. All of the code is public if you’d like the run it, and I created the ability for you to weigh likely/lean nos differently. That being said, they’re not creating very high estimates for many animals because there were relatively few “lean/likely no” judgments, we have many more models than just the pain/pleasure model that give lower welfare ranges, and we were quite conservative by assuming that all “Unknown” proxies were in fact absent. We’d love to have the chance to come up with new models using a more Bayesian framework, and in doing so, we might make different choices. But the point still holds that the models currently do not guarantee high welfare ranges. 
6. Speaking personally (though I know some others on the team agree), I also reject approaches to meta-normative uncertainty that can easily lead you to be dominated by one fanatical theory. If you resolve meta-normative uncertainty by maximizing choiceworthiness, you're equally susceptible to Pascal's mugging. So, if (like me) you don't want to go all-in on expected value maximization because of the Pascal’s mugging worry, you aren't going to accept strategies for resolving meta-normative uncertainty that recreate that exact problem. In this case, then, the argument that we should still think that nematode welfare dominates our calculations even if we put a small credence on total hedonic utilitarianism doesn’t move me that much. 

Overall, I encourage you and others on the EA Forum to not view our first version of the welfare range estimates as our final word on this. The book version, Weighing Animal Welfare, is more systematic, and we hope to improve on the methods in the future. But even still, I don’t think that the original version commits one to the view that very simple animals should dominate our calculations absent other highly controversial normative and meta-normative assumptions. 

Hi Vasco, 

Thanks for the question (as a researcher, I greatly appreciate the depth of your interest in our work!). It appears as though you're right about the mix-up in the formula in the spreadsheet you referenced, so I have corrected that. 

Importantly, however, I would note that the quantitative model is not one that we included in our welfare range estimates (it came from an earlier draft version of the project), and we wouldn't endorse using its results over our all-things-considered welfare range estimates that we've published here. 

Thanks again for the comment!

Hi Henry! The reason why the intervals are so wide is because they're mixing together several models. I've explained more about this modeling choice and result here: https://forum.effectivealtruism.org/posts/rLLRo9C4efeJMYWFM/welfare-ranges-per-calorie-consumption?commentId=Wc2xksAF3Ctmi4cXY