My understanding of the argument regarding “Meat reduction data from Germany's Statistical Office” is that significantly less meat is consumed in January than in the other months (I don't understand the argument in the sense that Veganuary has contributed to the downward trend over the years). Perhaps it would be better to compare the value for January 2023 with the monthly average for 2023 than with the monthly average for 2022, because this would rule out the possibility that the comparatively low consumption is due to the downward trend over the years. However, since the annual decline is less than 12.5% or 14.3%, consumption in January is also lower than the average month of the corresponding year.
The fact that the consumption of poultry meat in Germany has risen in recent years is very regrettable, but I don't believe that this is due to Veganuary. However, the German Statistical Office should also have figures for different animal species, so you should be able to see whether the consumption of poultry meat is higher, lower or similar in January compared to other months.
I don't think comparing January with December is very helpful because December is an atypical month due to Christmas.

If I understand correctly, you compare a donation to an animal welfare organization to an investment in alt protein? At least that is the case in the linked article. I find this comparison somewhat unfortunate, because with a donation the money is gone, with an investment (hopefully) not. A better comparison would be a donation to an animal welfare organization vs. a donation to e.g. the Good Food Institute, which uses the money to encourage more private or public investment.

Regarding displacement: Intuitively, I can't imagine that increased consumption of alt protein won't reduce meat consumption at the moment (to what extent I can't judge). In the long term, I'm pretty sure it will, because I think there's a kind of natural upper limit to total food consumption (apart from perhaps the possibility that more and more food will be thrown away).

My assumption was that player 1 and player 2 each have one year and can dedicate that year either to Intervention A or Intervention B. In the joint game, Player 1 would choose Intervention A if they were alone and Intervention B if Player 2 was also involved. If we always construct a joint game in this way—so that, depending on the coalition formed, the interventions are chosen and divided in a way that achieves the best overall outcome—then this joint game, by definition, leads to the best overall outcome.

Additionally, I am unclear on what "optimizing for cost-effectiveness in terms of Shapley value" is supposed to mean. In order to optimize something, there must be multiple options—so, multiple games, right? Even if we include the joint game, it would still be best for Player 2, in terms of the Shapley value, to play the game "Intervention A" with a Shapley value of 50.

But I think it’s not very useful to continue discussing this unless the claim "Agents individually optimizing for cost-effectiveness in terms of Shapley value globally optimize for total cost-effectiveness." is precisely defined.

Yes, it's a coordination problem. I understand the claim"Agents individually optimizing for cost-effectiveness in terms of Shapley value globally optimize for total cost-effectiveness." in the way that they don't coordinate but optimize individually. 

What about this example?
Intervention A
Value of {}: 0
Value of {1}: 0
Value of {2}: 0
Value of {1,2}: 100
-> Shapley value of 1 is: 50, shapley value of 2 is: 50.
Intervention B
Value of {0}: 0
Value of {1}: 60
Value of {2}: 0
Value of {1,2}: 60
-> Shapley value of 1 is: 60, shapley value of 2 is: 0.
Player 1 would go for intervention B, player 2 would go for intervention A. Result: value of A = 0; value of B = 60 -> total utility 60. It would be better if both players decide for A.

Assume that the invention of calculus has utility 100 and the invention of Shapley value has utility 10. Newton (player 1) can invest one year to invent calculus or invest one year to invent Shapley values. Leibniz (player 2) can invest 350 days to invent calculus or invest one year to invent Shapley values.
For the invention of calculus:

Shapley values for invention of calculus:
 

For the invention of Shapley values:
 

Shapley values for invention of Shapley values:
 

For both Newton and Leibniz the Shapley value is higher for the invention of calculus (50 compared to 5), so they both invent calculus. Overall result: +100 utility.
It would have been better if Leibniz had invented calculus and Newton had invented Shapley values in that time. Overall result: +110 utility.

Improved approach: "One solution would be to first decide for the project with the highest cost-effectiveness (in Shapley value) and then recalculate the Shapley values."
The project with the highest cost-effectiveness (in Shapley value) is that Leibniz invents calculus (Shapley value = 50 / 350 days). So Leibniz will invent calculus. Now, the Shapley values are recalculated. Leibniz only has 15 days left in that year. That's not enough for inventing Shapley values. 

For the invention of calculus (it is already invented by Leibniz, so no additional benefit):

Shapley values for invention of calculus:

For the invention of Shapley values (Leibniz does not have enough time):

Shapley values for invention of Shapley values:
 

So, Newton would decide to invent Shapley values (Shapley value = 10 compared to Shapley value = 0 when inventing calculus).

Overall result: +110 utility.

PS. Sorry, I don't know how to make the screenshots smaller...

On Nuance in Scale:

I actually found the point about the number of lab mice/rats quite interesting—I wasn’t really aware of it before, even though I did know that mice and rats make up the majority of lab animals and that the total number of farmed land animals is dominated by chickens.

Overall, however, I believe that the proxies mentioned here are quite reasonable. Specifically, in defense of them, I would add:

• Minority farmed animals vs. majority lab animals: Work on farmed cows will also raise public awareness about the living conditions of farmed animals in general, which will ultimately benefit other species (e.g., chickens).
• The number of animals in a region vs. the number of animals affected: It is always preferable to prioritize interventions that reach a large percentage of animals in a given country over those that do not. Even if some of these interventions have not yet been widely tested in certain countries or may not be directly implementable in the same way as in Western countries, a stronger focus on, for example, China could also lead to the discovery of large-scale intervention strategies within the country itself.
• Farmed animals vs. wild animals: Generally, there are still many unresolved questions regarding wild animal suffering. However, I don’t think anyone claims that the number of animals is the sole determining factor in prioritization—it is simply one of several factors.

Very nice text, thank you for writing it!!
I’m not sure whether this statement is universally true (and I’m also not entirely clear on what exactly it means):
"Agents individually optimizing for cost-effectiveness in terms of Shapley value globally optimize for total cost-effectiveness."

Let’s take Example 2: If the invention of calculus had a very large benefit, then both Newton and Leibniz optimized their cost-effectiveness in terms of Shapley value by working on it. However, the global cost-effectiveness would have been higher if only one of them had made the invention and the other had contributed to something else valuable instead.

One solution would be to first decide for the project with the highest cost-effectiveness (in Shapley value) and then recalculate the Shapley values. In that case, either Newton or Leibniz would work on the invention of calculus (depending on who had lower costs), and the other would not. But there are still situations where this approach does not lead to the highest cost-effectiveness (if the Shapley value is based on coalitions that are unrealistic due to limited available resources):

Let's assume that the three charities A, B, and C can finance a campaign for better chicken welfare with $1m. If only Charity A runs the campaign, it helps 200,000 chickens, and the same applies to Charity B. If Charities A and B launch a joint campaign, it helps 600,000 chickens. Charity C can only work alone and would help 250,000 chickens.

If a donor had $1m available, they would have to choose Charity A or B according to the Shapley value (300,000 chickens), but in reality, they would only help 200,000 chickens (assuming that a joint campaign by Charity A and B with $0.5m each is not possible or would also only help 200,000 chickens). It would be better to give the $1m to Charity C and help 250,000 chickens.

Thank you, @Kevin Xia 🔸 , for the text!
I also find the Shapley value very interesting for attributing impact—I wasn't familiar with it before, so thanks for the hint, @Vasco Grilo🔸 !

I think it depends on what decisions are being guided by the "impact share." If the goal is to determine how a donor should allocate their money, then in your first example, the Shapley value is probably more suitable than simple counterfactuals. However, if Organization A has already decided that it has fulfilled its role in securing a corporate commitment and now Organization B is deciding whether to do the same, then counterfactuals are useful here (which are identical to Shapley values with only one actor).

Even though the Shapley value is a good reference point for donors when distributing funds, I don’t think the best overall strategy is necessarily to donate to the charities with the highest cost-effectiveness in terms of Shapley value. Instead, donations should also be "coordinated." This becomes particularly clear in the second example: If Organization A and Organization B had nearly the same costs for referring to a grant, their cost-effectiveness would also be nearly the same, and a donor would most likely have to support either no charity or both charities for that purpose. It is obviously smarter to fund only one (or none) of them in this case.

One solution would be to first fund the project with the highest cost-effectiveness (in Shapley value) and then recalculate the Shapley values. In the second example, this would mean that first, Organization A or Organization B is funded (whichever has slightly lower costs), and then the other organization is no longer funded for this purpose.

However, in the first example, problems could arise if the total donation budget is insufficient to fund both organizations, meaning that in the end, the money has no effect at all.

Even though this scenario may seem unrealistic (since Organization A’s actions would likely still have a positive impact, even if Organization B does nothing), this problem also appears in a slightly modified model that may be more realistic. Let’s assume that if Organization A or Organization B acts alone, they would help 200,000 chickens. The Shapley value per organization would still be 300,000 chickens, but if the funds are not sufficient to support both organizations, funding one of them would only help 200,000 chickens. In that case, it would be better to fund a third charity, Charity C, which could help 250,000 chickens (in Charity C’s campaign, no other organizations would play a role).

Hi Engin, thanks for your reply!
I agree that it's better to have multiple major donors than one major donor (e.g. it's better to have four major donors who contribute to 20% of all funding each; than one major donor who gives 80% of all funding). I would assume that EAAWF and ACE rely on smaller donors who would have donated invidually otherwise. So in the case that - for example - there is one major donor (60%) and many small donors (summing up to 40%), I don't know if it's good to pool the money of the small donors by ACE or EAAWF (as long as they donate to equally effective charities) so that there are one major donor (60%), and e.g. ACE and EAAWF as further major donors (each 20%). On the one hand, it's easier for ACE and EAAWF to react to a cut of funding by the major donor. On the other hand, there will probably be many charities which depend on ACE or EAAWF instead of many small donors. Of course, if the total amount of donations increases by new major donors, it's a different thing.

You write that Funds like ACE or the EA Animal Welfare Fund can be a solution to the coordination problem when financial cutbacks are necessary (and you don't want to apply across-the-board cuts). That's true, but such funds also create exactly the dependencies on a few large donors that you criticize in the text, don't they? This dependency wouldn't exist if the money came directly from many small donors.

In general, one could say that ACE and EAAWF are better informed than individuals (also regarding the question of which organizations are particularly effective), but the same could be said about OP. I also find that plausible in principle, but I also think that a certain degree of "democratization" makes sense because it reduces the risk of wrong decisions and keeps a public discussion about effectiveness ongoing, which ultimately (hopefully) leads to better identification of more effective measures.

A lower dependency on major donors could also be good if we assume that (at least in some situations) the organizations themselves are better able than the large donors to assess which measures are most effective. With a high dependency, they might implement the measures preferred by the major donor, even though they actually believe that other measures would be more effective.

And then there are the arguments mentioned in the text. Can the arguments be summarized in such a way that the main problem of fragility is that larger fluctuations in financial resources are to be expected, and in the event of significant cutbacks, structures, experiences, and security that have been built up over years would be lost, and rebuilding them would come with additional costs?