Thanks for the post, Matthew! Very funny and heart-warming.

I estimate that when someone experiences profound love, their increased wellbeing leads to approximately 2.3 % (= 50 additional kcal consumed per day * 0.046 % per kcal) additional food consumption. Multiplying this by the roughly 4.71*10^13 soil nematodes affected per kcal of food production (from my back-of-the-envelope calculations based on van den Hoogen et al. (2019)), I get approximately 1.08*10^12 affected nematode-years per year of experiencing love. Conditional on my preferred exponent of the number of neurons of 0.7, and assuming the welfare range of a nematode is 10^-6 as a fraction of that of humans, the welfare effects on soil animals could be 1.08*10^6 nematode-equivalent quality-adjusted life years (QALYs) per year of love experience.

Very interesting Fermi estimate. I was actually wondering about how many nematode-years were affected by 1 kcal just a few days ago, although not in the context of love. Claude's numbers are quite off. Here is my version. Rice requires 0.00164 m^2-years per kcal. I very roughly estimate crops have 1.33 M soil nematodes per m^2, and other biomes besides pasture, and deserts and xeric shrublands have 1.72 M to 9.31 M soil nematodes per m^2. So I calculate increasing the area of crops by 1 m^2-year decreases 390 k (= (1.72 - 1.33)*10^6) to 7.98 M soil-nematode-years (= (9.31 - 1.33)*10^6). I am very uncertain about whether increasing cropland increases or decreases soil-nematodes-years. So my actual takeaway is more that increasing the area of crops by 1 m^2-year increases or decreases 390 k to 7.98 M soil-nematode-years. As a result, I calculate 1 kcal of rice increases or decreases 640 (= 0.00164*390*10^3) to 13.1 k soil-nematode-years (= 0.00164*7.98*10^6). In words, a few thousands of soil-animal-years per kcal of rice.

For Claude's assumption that profound love increases energy intake by 50 kcal/profound-love-day, and this being satisfied by consuming rice, I get a change of 32.0 k (= 640*50) to 655 k soil-nematode-years per profound-love-day (= 13.1*10^3*50), or 11.7 M (= 32.0*10^3*365.25) to 239 M soil-nematode-years per profound-love-year (= 655*10^3*365.25). In words, tens of thousands to hundreds of thousands of soil-nematode-years per profound-love-day.

Claude estimated 1.08 trillion soil-nematode-years per profound-love-year, 4.52 k (= 1.08*10^12/(239*10^6)) times my upper bound. I wonder how Claude can get these relatively simple calculations so off.

Thanks for the great post, Sofia. I would just focus on increasing animal welfare instead of ending factory farming. I think more happiness and less suffering are necessarily good (all else equal), whereas I do not see large scale intensive animal farming as necessarily bad. I estimate slower growth broilers, and hens in cage-free aviaries have negative, but close to neutral lives.

Thanks for clarifying, Arvo.

We didn't find that people were responding with zero plausibility very much at all.

I wonder how people decided between a plausibility of 0/10 and 1/10. It could be that people picked 0 for a plausibility lower than 0.5/10, or that they interpreted it as almost impossible, and therefore sometimes picked 1/10 even for a plausibility lower than 0.5/10. A logarithmic scale would allow experts to specify plausibilities much lower than 1/10 (e.g. 10^-6/10) without having to pick 0, although I do not know whether they would actually pick such values.

I'm not sure what you have in mind in terms of modelling the stances' weight as distributions instead of point estimates. Perhaps you mean something like leveraging those distributions above via some sort of Monte Carlo where weights are drawn from these distributions and the process is repeated many times, then aggregated.

Yes, this is what I had in mind. Denoting by W_i and P_i the distributions for the weight and probability of consciousness for stance i, I would calculate the final distribution for the probability of consciousness from (W_1*P_1 + W_2*P_2 + ... W_13*P_13)/(W_1 + W_2 + ... W_13).

That indeed sounds more sophisticated and could possibly help track uncertainty but I suspect it would very little difference. In particular, I think so because we observed that unweighted pooling of results across all stances is surprisingly similar to the pool when weighted by experts; the same if you squint.

I think the mean of the final distribution for the probability of consciousness would be very similar. However, the final distribution would be more spread out. I do not know how much more spread out it would be, but I agree it would help track uncertainty better.

Thanks for the post, Moritz. I liked it.

I would model the weights of the models as very wide distributions to represent very high model uncertainty.

In particular, I would model the weights of the stances as distributions instead of point estimates. As you note in the report, there was lots of variation across the 13 experts you surveyed

I wonder what exactly you asked the experts. I think the above would underestimate uncertainty if you just asked them to rate plausibility from 0 to 10, and there were experts reporting 0. Have you considered having a range of possible responses in a logarithmtic scale ranging from a weight/probability of e.g. 10^-6 to 1?

Thanks, Angelina. Happy preparation of EAG SF.

Thanks for sharing, Angelina.

It is nice to see significant growth of the number of subscribers over 2025, especially considering the downwards trend over 2023 and 2024.

I agree "flow" metrics are a better proxy for current impact, and that the number of actively engaged subscribers is a better metric than the number of subscribers.

Thanks for clarifying, Diego. I would be happy to review the cost-effectiveness analysis (CEA) for free if you want.

Hi Rory. That is great to know. I am looking forward to what you come up with.

I like the dashboard because it is a way of quickly getting a rough sense of the impact of CEA's programs. The number of people engaging in each tier may well track progress better, but they cannot be so easily interpreted as concrete metrics like the number of subscribers of the EA newsletter.

I think it would also be helpful to see the number of people engaging in each tier across time. There are numbers in the post for 2024 and 2025, and the numbers for 2025 were better than for 2023 ("reversing the moderate decreases in engagement with our programs throughout 2023-2024"). However, the meaning of this depends on the stability of past trends. Many past annual changes in engagement up or down of 10 % to 20 % would make a 25 % increase from 2024 to 2025 less impressive relative to a past downwards trend of a few years.