Saving human lives cheaply is the most cost-effective way of increasing animal welfare?

By Vasco Grilo🔸 @ 2025-08-07T16:29 (+7)

Summary

• I estimate the cost-effectiveness accounting for target beneficiaries, and soil ants, termites, springtails, mites, and nematodes. I suppose the welfare range, the difference between the maximum and minimum welfare per unit time, is a power law of the number of neurons. In particular, I use welfare ranges as a fraction of that of humans equal to “number of neurons as a fraction of that of humans”^“exponent of the number of neurons”, with the exponent ranging from 0 to 2. I analyse cage-free corporate campaigns, buying beef, broiler welfare corporate campaigns, GiveWell’s top charities, Centre for Exploratory Altruism Research’s (CEARCH’s) High Impact Philanthropy Fund (HIPF), and Shrimp Welfare Project’s (SWP’s) Humane Slaughter Initiative (HSI).
• Rethink Priorities’ (RP’s) moral weight project included a report by Adam Shriver concluding “there is no straightforward empirical evidence or compelling conceptual arguments indicating that relative differences in neuron counts within or between species reliably predicts welfare relevant functional capacities”. I guess there are other factors besides the number of neurons that influence the welfare range. However, I estimate an exponent of 0.188 explains 98.2 % of the variance of the estimates in Bob’s book containing what RP stands behind now (see 1st graph). So I prefer to rely on a simple formula to decrease noise, and easily obtain estimates for animals not covered in the book to explore implications for cause prioritisation.
• The effect on soil ants, termites, springtails, mites, and nematodes is much larger than that on the target beneficiaries for an exponent of the number of neurons lower than 1, in which case the welfare range is less than proportional to the number of neurons. Moreover:
  • Even for an exponent of 1, in which case the welfare range is proportional to the number of neurons, and chicken welfare corporate campaigns increase the welfare of chickens roughly as cost-effectively as SWP’s HSI has increased the welfare of shrimp (see the 3rd graph), the increase in the welfare of soil ants, termites, springtails, mites, and nematodes as a fraction of the increase in the welfare of the target beneficiaries is:
    • For cage-free corporate campaigns, 1.48.
    • For buying beef, 12.1 k.
    • For broiler welfare corporate campaigns, 23.3.
    • For GiveWell’s top charities, 41.5.
    • For HIPF, 32.5.
  • The above ratios are much larger for an exponent of 0.19 which almost perfectly explains RP’s preferred welfare ranges:
    • For cage-free corporate campaigns, 77.8 k.
    • For buying beef, 4.92 billion.
    • For broiler welfare corporate campaigns, 1.22 M.
    • For GiveWell’s top charities, 263 M.
    • For HIPF, 206 M.
• I continue to recommend funding HIPF, which is the most cost-effective intervention among the ones I analysed for any exponent of the number of neurons. In addition, for my preferred exponent of 0.5, I estimate:
  • Cage-free corporate campaigns are 1.14 % as cost-effective (as funding HIPF).
  • Buying beef is 3.72 % as cost-effective.
  • Broiler welfare corporate campaigns are 6.51 % as cost-effective.
  • GiveWell’s top charities are 10.6 % as cost-effective.
  • SWP’s HSI has been 0.0292 % as cost-effective.
• I do not recommend funding interventions targeting farmed invertebrates. I think SWP’s HSI is among the most cost-effective of these accounting only for target beneficiaries, and it has been the least cost-effective intervention among the ones I analysed by far for any exponent of the number of neurons accounting for target beneficiaries, and soil ants, termites, springtails, mites, and nematodes.
• I recommend investigating whether soil ants and nematodes have positive or negative lives, starting with soil nematodes. I estimate effects on soil ants account for most of the effects on soil ants, termites, springtails, mites, and nematodes for all the interventions I analysed for an exponent of the number of neurons of 1.38 or higher, and that effects on soil nematodes account for most of those effects for all the interventions I analysed for an exponent of 1.18 or lower. I supposed soil nematodes have negative lives, but can easily see them having positive lives, and would conclude all the interventions I analysed besides SWP’s HSI are harmful (instead of beneficial) in this case.

Methods

I estimated the cost-effectiveness of a few interventions accounting for target beneficiaries, and soil springtails, mites, and nematodes based on the welfare ranges as a fraction of that of humans RP initially presented. Meanwhile, Bob Fischer, who led RP’s moral weight project, said on July 28 that “What we [RP] stand behind now is really just what we published in the book [the one I mentioned in the summary; here is a comparison between the book’s and RP’s initial estimates for the welfare ranges]”. The tentative estimates presented in Chapter 8 were obtained aggregating the welfare ranges conditional on sentience as a fraction of that of humans of 3 models, the equality, neurophysiological, and simple additive models, which are weighted at 10 %, 30 %, and 60 %. An organism without any neurons has a welfare range conditional on sentience as a fraction of that of humans under the neurophysiological of 0, but this only directly limits the welfare range conditional on sentience as a fraction of that of humans to 0.7 (= 1 - 0.3). I guess the absence of neurons directly limits the welfare range conditional on sentience as a fraction of that of humans much more. I guess it is better to assume the contribution of non-structural properties to the welfare range as a fraction of that of humans is moderated by structural properties.

In this post, I estimate the cost-effectiveness accounting for target beneficiaries, and soil ants, termites, springtails, mites, and nematodes. I suppose the welfare range, the difference between the maximum and minimum welfare per unit time, is a power law of the number of neurons. In particular, I use welfare ranges as a fraction of that of humans equal to “number of neurons as a fraction of that of humans”^“exponent of the number of neurons”, with the exponent ranging from 0 to 2. I analyse cage-free corporate campaigns, buying beef, broiler welfare corporate campaigns, GiveWell’s top charities, CEARCH’s HIPF, and SWP’s HSI.

RP’s moral weight project included a report by Adam Shriver concluding “there is no straightforward empirical evidence or compelling conceptual arguments indicating that relative differences in neuron counts within or between species reliably predicts welfare relevant functional capacities”. I guess there are other factors besides the number of neurons that influence the welfare range. However, I estimate an exponent of 0.188 explains 98.2 % of the variance of the estimates in Bob’s book containing what RP stands behind now (see 1st graph). So I prefer to rely on a simple formula to decrease noise, and easily obtain estimates for animals not covered in the book to explore implications for cause prioritisation. I get that exponent from the slope of a linear regression with null intercept of the logarithm of RP’s preferred welfare range as a fraction of that of humans on the logarithm of the number of neurons as a fraction of that of humans

My formula for the welfare range as a fraction of that of humans implies a welfare range as a fraction of that of humans of 0 for organisms without neurons, which I think is an underestimate, as I am not certain they have a constant welfare per unit time as a result of not having neurons. Furthermore, I speculate effects on microorganisms, which do not have neurons, are much larger than those on soil animals, although positively correlated.

I calculate the increase in the welfare of the target beneficiaries per $ by multiplying my past estimates by my updated welfare range of the target beneficiaries as a fraction of that I used to obtain them.

I suppose 0.25 animal-years of fully happy soil ants/termites/springtails/mites/nematodes neutralise 1 animal-year of random soil ants/termites/springtails/mites/nematodes. Karolina Sarek, Joey Savoie, and David Moss estimated 0.42 for the “wild bug” in 2018, which implies a welfare further from 0 (more negative) than I assumed (0.42 > 0.25).

I get the number of soil ants, termites, springtails, and mites per unit area for 10 biomes using the means in Table S4 of Rosenberg et al. (2023). I determine the number of soil nematodes per unit area by multiplying the number of soil arthropods from this table by 48.9, which is my estimate for the ratio between the number of soil nematodes and soil arthropods globally.

I use my past estimates for the increase in agricultural land per $. Nevertheless, instead of assuming additional agricultural land is cropland replacing a single biome, as I did before, I consider a mix of cropland and pastures replacing a mix of biomes in proportions guessed by Gemini 2.5 on 2 August 2025. I assume HSI’s effects on soil ants, termites, springtails, mites, and nematodes are negligible compared with those on shrimp because it does not change the amount of feed-kg per food-kg, unlike cage-free and broiler welfare corporate campaigns.

Here are my calculations.

Results

Linear regression with null intercept of the logarithm of RP’s preferred welfare range as a fraction of that of humans on the logarithm of the number of neurons as a fraction of that of humans

An exponent of the number of neurons of 0.188, corresponding to the slope of the line below, explains 98.2 % of the variance in RP’s preferred welfare. An exponent of 0.188 means the number of neurons has to increase by 5.32 (= 1/0.188) orders of magnitude (OOMs), becoming 209 k (= 10^5.32) times as large, for the welfare range to increase by 1 OOM. RP’s preferred welfare ranges of shrimp and black soldier flies (BSF), the animals with the least neurons by far covered in Bob’s book, are 86.0 k and 17.9 k times those implied by an exponent of 1.

Welfare range of the target beneficiaries as a fraction of that of humans

The welfare range of the target beneficiaries decays faster (with the exponent of the number of neurons) for ones with fewer neurons. The slope of the straight lines below is the logarithm of the number of neurons as a fraction of that of humans.

Increase in the welfare of the target beneficiaries

I believe one should consider effects on soil ants, termites, springtails, mites, and nematodes. However, accounting only for the target beneficiaries, prioritisation among the interventions I have analysed besides buying beef matters the least for an exponent of the number of neurons ranging from 0.86 to 1, where the ratio between the highest and lowest cost-effectiveness among those interventions is 12.0.

Increase in the welfare of soil ants, termites, springtails, mites, and nematodes

The increase in the welfare of soil soil ants, termites, springtails, mites, and nematodes per unit area is similar for all interventions because Gemini 2.5 guessed the additional agricultural land would replace biomes in approximately the same way. In reality, there is variation even within a single type of intervention.

Increase in the welfare of soil ants as a fraction of the increase in the welfare of soil ants, termites, springtails, mites, and nematodes

The effect on soil ants is the major driver of the effects on soil ants, termites, springtails, mites, and nematodes for a high exponent of the number of neurons because they have the most neurons per individual among those animals.

Increase in the welfare of soil termites as a fraction of the increase in the welfare of soil ants, termites, springtails, mites, and nematodes

Buying beef is the only intervention I analysed increasing the welfare of soil termites. However, crops and pastures have the least soil ants/springtails/mites/nematodes per unit area besides deserts, and xeric shrublands, which would very hardly be replaced by the additional agricultural land, and effects on soil termites account for a tiny fraction of the effects on soil ants, termites, springtails, mites, and nematodes for an exponent of the number of neurons lower than 1, which I endorse. So I conclude the welfare of those animals considered together would still decrease for land use changes different from the ones guessed by Gemini.

Increase in the welfare of soil nematodes as a fraction of the increase in the welfare of soil ants, termites, springtails, mites, and nematodes

The effect on soil nematodes is the major driver of the effects on soil ants, termites, springtails, mites, and nematodes for a low exponent of the number of neurons because they have the least neurons per individual among those animals.

Increase in the welfare of soil ants, termites, springtails, mites, and nematodes

There is some variation in the increase in the welfare of soil ants, termites, springtails, mites, and nematodes per $ across interventions. Yet, there is way more variation with the exponent of the number of neurons within a single intervention.

Increase in the welfare of soil ants, termites, springtails, mites, and nematodes as a fraction of the increase in the welfare of the target beneficiaries

The effect on soil ants, termites, springtails, mites, and nematodes is much larger than that on the target beneficiaries for an exponent of the number of neurons lower than 1, in which case the welfare range is less than proportional to the number of neurons. Moreover:

• Even for an exponent of 1, in which case the welfare range is proportional to the number of neurons, and chicken welfare corporate campaigns increase the welfare of chickens roughly as cost-effectively as SWP’s HSI has increased the welfare of shrimp (see the 3rd graph), the increase in the welfare of soil ants, termites, springtails, mites, and nematodes as a fraction of the increase in the welfare of the target beneficiaries is:
  • For cage-free corporate campaigns, 1.48.
  • For buying beef, 12.1 k.
  • For broiler welfare corporate campaigns, 23.3.
  • For GiveWell’s top charities, 41.5.
  • For HIPF, 32.5.
• The above ratios are much larger for an exponent of 0.19 which almost perfectly explains RP’s preferred welfare ranges:
  • For cage-free corporate campaigns, 77.8 k.
  • For buying beef, 4.92 billion.
  • For broiler welfare corporate campaigns, 1.22 M.
  • For GiveWell’s top charities, 263 M.
  • For HIPF, 206 M.

Increase in the welfare of the target beneficiaries, and soil ants, termites, springtails, mites, and nematodes

HIPF is much more cost-effective than the other interventions for any exponent of the number of neurons. The slope of the cost-effectiveness of all interventions besides the past work of SWP’s HSI becomes less negative once the effects on the target beneficiaries start to dominate, since these have more neurons than soil ants, termites, springtails, mites, and nematodes.

Results for my preferred welfare ranges

Below are the results for my preferred welfare ranges respecting an exponent of the number of neurons of 0.5. “E+” stands for “*10^”. My exponent is significantly higher than the value of 0.188 which I estimate explains 98.2 % of the variance in RP’s preferred estimates. So my exponent implies the welfare range increases much closer to linearly with the number of neurons, although still significantly sublinearly.

There is variation in the cost-effectiveness of each of the above interventions, and therefore picking the most cost-effective opportunities within each type matters. For example, funding the most cost-effective instead of random cage-free corporate campaigns may be more important than funding random broiler welfare corporate campaigns instead of random cage-free corporate campaigns.

My recommendations

I continue to recommend funding HIPF, which is the most cost-effective intervention among the ones I analysed for any exponent of the number of neurons. In addition, for my preferred exponent of 0.5, I estimate:

• Cage-free corporate campaigns are 1.14 % as cost-effective (as funding HIPF).
• Buying beef is 3.72 % as cost-effective.
• Broiler welfare corporate campaigns are 6.51 % as cost-effective.
• GiveWell’s top charities are 10.6 % as cost-effective.
• SWP’s HSI has been 0.0292 % as cost-effective.

I do not recommend funding interventions targeting farmed invertebrates. I think SWP’s HSI is among the most cost-effective of these accounting only for target beneficiaries, and it has been the least cost-effective intervention among the ones I analysed by far for any exponent of the number of neurons accounting for target beneficiaries, and soil ants, termites, springtails, mites, and nematodes.

I recommend investigating whether soil ants and nematodes have positive or negative lives, starting with soil nematodes. I estimate effects on soil ants account for most of the effects on soil ants, termites, springtails, mites, and nematodes for all the interventions I analysed for an exponent of the number of neurons of 1.38 or higher, and that effects on soil nematodes account for most of those effects for all the interventions I analysed for an exponent of 1.18 or lower. I supposed soil nematodes have negative lives, but can easily see them having positive lives, and would conclude all the interventions I analysed besides SWP’s HSI are harmful in this case.

My recommendations are supposed to hold under my AI timelines. I like Ege Erdil’s median time of 20 years until full automation of remote work, and I would not neglect impact after this. CEARCH granted 63 k$ to decrease the consumption of sugar-sweetened beverages (SSBs) to decrease the burden of diabetes mellitus type 2 (DMT2), and 150 k$ to decrease the consumption of sodium (in salt) to decrease the burden of high systolic blood pressure (HSBP) until 27 May 2025, and the burden per capita of DMT2 has been increasing, and that of HSBP has been stable despite an increasing real gross domestic product (real GDP) per capita. However, I would recommend buying beef, or funding broiler welfare corporate campaigns or HIPF only accounting for effects over the next 10 years. In this case:

• I guess funding HIPF would become 3.88 % as cost-effective. I estimate advocacy for taxing SSBs would become 3.88 % as cost-effective.
• I expect buying beef would remain as cost-effective as before, 95.9 % (= 0.0372*1/0.0388) as cost-effective as funding HIPF. I guess the vast majority of its impact materialises in less than 10 years.
• I calculate broiler welfare corporate campaigns would become 75 % (= (10 - 2.5)/10) as cost-effective, 1.26 (= 0.0651*0.75/0.0388) times as cost-effective as funding HIPF. I guess they accelerate welfare reforms by 10 years, and have an impact linearly increasing from affecting no to all broilers over 5 years, which is equivalent to starting affecting all broilers in 2.5 years (= 5/2).

Acknowledgements

Thanks to Michael St. Jules for feedback on the draft. The views expressed in the post are my own.