I am open to work.
Vasco Grilođ¸
[Question] EffecÂtive givÂing iniÂtiÂaÂtives should not asÂsume the best anÂiÂmal and huÂman welfare inÂterÂvenÂtions are equally cost-effecÂtive?
I believe the effects of Cool Earth on animals can easily dominate those on humans
I estimate the harm a random person caused to poultry birds and farmed aquatic animals in 2022 was 217 times the harm their GHG emissions caused to humans.
Thanks a lot, Ulf!
I am very curios about how you would like the world to look like, what would your utopia be?
Thanks for the question! I strongly endorse expectational total hedonistic utilitarianism (maximising happiness, and minimising suffering), so my ideal world would have as much expected total hedonistic welfare as possible.
Nearterm, I would like people to consider digital sentience, factory-farming, and wild animal suffering the most pressing issues of our time (I have ordered them alphabetically). More importantly, I would like people to donate more to the Arthropoda Foundation, SWP or WAI. I think these are the organisations which more cost-effectively increase welfare. In addition, I believe increasing the donations to those organisations is the best strategy to maximise impact for the vast majority of people, even among people working in impact-focussed organisations.
Longterm, I would like the world to be filled with beings which have the most welfare per energy consumed. I estimate bees can experience 4.88 k times as much welfare per calorie consumption as humans. My estimates for the 5th and 95th percentile are 0 and 31.7 k, so I am not confident filling the universe with bees would be better than filling it with humans. Moreover, there may be other species or non-biological beings which experience even more welfare per energy consumed than bees. However, I would be surprised if humans were the beings experiencing the most welfare per energy consumption.
Thanks for another insightful comment, Ulf!
I think your thoughts about cause prioritisation are very interesting, and they have made me talk about animal suffering and effectiveness when I hold a lecture for my students in public health.
Great to know!
I donate money to Cool Earth because they address biodiversity, climate change and poverty.
I worry efforts to preserve biodiversity may be harmful due to encouraging wildnerness preservation, and therefore increasing wild animal suffering. I also think fighting climate change may be harmful due to increasing wild animal suffering. I would even say helping people in poverty may be harmful via increasing factory-farming. I believe the effects of Cool Earth on animals can easily dominate those on humans, and there is lots of uncertainty about whether the effects on animals are positive or negative, so I do not know whether Cool Earth is overall beneficial or harmful. Relatedly:
I believe the large uncertainty about the effects of human welfare interventions on wild (and farmed) animals should push one towards prioritising:
Animal welfare interventions improving the conditions of animals instead of decreasing the number of animals with negative lives, or increasing the number of animals with positive lives. I recommend donating to the Shrimp Welfare Project (SWP), which I estimate has been 64.3 k times as cost-effective as GWâs top charities (neglecting their effects on animals).
Learning more about helping invertebrates, whose total capacity for welfare vastly exceeds that of vertebrates. I recommend donating to (I ordered the organisations alphabetically):
The Arthropoda Foundation. Their research priorities are humane slaughter protocols, stocking densities and substrate research, and automated welfare assessment.
The Wild Animal Initiative (WAI). For instance:
They intend âto use current and new fundingâ for, among other activities, âConducting an analysis of agricultural pest control to better understand the best targets for welfare interventions â first identifying scientific gaps and then developing research plans to help fill themâ.
I estimate paying farmers to use more humane pesticides to decrease the suffering of wild insects is 23.7 k times as cost-effective as GWâs top charities.
First of all, I want to thank you for your posts. Many of them have given me new perspectives and knowledge that I appreciate.
Thanks, Ulf! I appreciate you sharing relevant links too. I strongly upvoted your comment.
I cannot open the above link.
Many rich people use tax havens (but most donât) for avoiding taxes.
Even then, in the United States (US), âThe top quintile funded 90.1 percent, or $1.6 trillion, of all government transfers in 2019â.
Another problem is when rich people use their wealth for lobbying, changing public opinion, changing politics in ways that makes the poor poorer and the rich richer.
I do not know whether taxing people with higher income more heavily would increase human welfare. I agree it would nearterm, as 1 $ results in a greater increase in welfare for people with lower income. However, my sense is that economists tend to agree that income and capital taxes decrease the growth of real gross domestic product (real GDP) per capita, which is strongly correlated with median income across countries. At least in the US, there has also been a strong correlation between mean and median income. So I expect taxing people with higher income more heavily via income and capital taxes would lead to a slower growth of the median income, which may decrease welfare longterm.
An example below is a comparison between the United States and Sweden.
I would need a more comprehensive analysis to be persuaded. Singaporeâs tax revenue was 11.5 % of its GDP in 2022, less than USâ 26.8 %, and much less than Swedenâs 43 %, but Singapore is much closer to Sweden than the US in terms of social outcomes.
There is a good correlation between self-reported life satisfaction and real GDP per capita across countries. So, since I think taxing people with higher income more heavily via income and capital taxes would slow down the growth of real GDP per capita, I worry it may lead to less welfare longterm.
Zooming out, I also care about the effects on animals. So I would want to know how taxing people with higher income more heavily would affect the consumption of animal-based foods, and development of alternative proteins to come to an overall view about whether people with higher income should be taxed more or less. I believe the 3 animal-based foods which account for the most animal suffering, ordered from the least to the most expensive, are chicken meat, fish, and shrimp. In high income countries, where even people with low income eat lots of animal-based foods, I guess taxing people with higher income more heavily would tend to decrease the consumption of chicken, but increase that of fish and shrimp (and beef, but I am not worried about this one).
Given my large uncertainty about how taxes affect welfare, I am currently deferring to the libertarian intuitions described in another post from Michael Huemer, Tax Breaks for the Rich.
The current system is like this: Five friends go out for dinner. Say they have some expenses that are common to the group (e.g., a shared appetizer) plus some items ordered by and for specific individuals. At the end of the meal, someone suggests that one of the friends, the one with the most money, should be forced to pay for everyone, even though he doesnât want to.
In the US, âThe top quintile funded 90.1 percent, or $1.6 trillion, of all government transfers in 2019â. So, if each of the 5 friends corresponded to one quintile, the richest one would pay for 90.1 % of the meal. I agree with Michael that:
Intuitively, a fair division would be like this: Everyone pays for the items that he himself ordered, plus 1â5 of the common items.
I am happy to answer if you have any questions.
Thanks for that! I think donations are the best way for people to increase their social impact. So, instead of discussing the effects of taxes, I would be curious to know your thoughts on my cause prioritisation. In particular, my view that the best animal welfare organisations are over 100 times as cost-effective as the best ones in human welfare. Have you considered donating to animal welfare?
Hi Nick.
Unfortunately this comment (rightly or wrongly) has made me think less of you and doubt the integrity of some of your other arguments and comments. I feel like its important for someone here to say publically that I strongly disagree with this line of thinking and find it abhorent and a horrible way to look at the world, and people who are far worse of than us.
I have published 2 posts arguing for people to donate to people in extreme poverty, and I have donated to organisations helping them too. I only started worrying about the meat-eating problem much later.
Many of the poor are not pulling their own weight, while the wealthy are pulling much more than their weight.
This sentence of the post relates to the following earlier claims.
Wealthy people â say, the top 20% of income earners â are paying almost all of the net tax burden. The bottom 40% are consuming much more government resources than they are paying in, and thatâs paid for by the top quintile.
These are accurate at least for the United States. âThe top quintile funded 90.1 percent, or $1.6 trillion, of all government transfers in 2019â.
The bottom quintile receives 1.27 $ from the government, 90.1 % of which come from the top quintile, for each 1 $ they spend. I am thankful to people who give me money regardness of their income. I do not know why this would not apply to people with low income.
I see no reason why my super poor friends here in the village in Uganda should be âthanking the richâ. The world has developed around them, and their quality of life has not improved to the extent that it should have, given how many resource there are in this world.
I do not know about the situation in Uganda. It may not be analogous to that in the United States.
Thanks, Nick.
At the level of the nation state, which is what matter socially, inequality has drastically increasedâespecially right at the top end of wealth.
I would say hapiness is more important than wealth, and it looks like hapiness inequality has decreased within countries (see graph in my 1st reply).
Hi there. The Gini coefficient of gross income has decreased a little over the last few decades globally, which means decreased inequality, and I believe the Gini coefficient is one of the best indicators of inequality due to accounting for the whole income distribution.
Our World in Data did not have data on the global trend of the Gini coefficient of net income, which is more relevant than gross income. However, hapiness is even more relevant, and hapiness inequality has apparently been decreasing.
ďRich and Poor: How Things Work
I noted Table 1 of the doc does not have the probability of sentience of shrimp, although I guess it is similar to that of crayfish, 45.3 %.
Thanks for sharing, Holly!
There was an increase in survey respondentsâ self-reported likelihood to support our cause after engaging with our campaign materials, with a 28.6% increase for âvery likelyâ and a 3% increase for âsomewhat likely.â
It would be great if you eventually estimated how much campaigns like this increase donations to the organisations recommended by ACE.
Thanks for the comment, Wladimir!
The Cumulative Pain analyses assume that the range of pain intensities varies from No-Pain to Excruciating in any sentient species. This range is needed in the method to make it flexible and adaptable across diverse taxa.
I have one question related to this. Feel free to reply there.
Nevertheless, I personally believe that the range of different intensities of affective experiences evolved to match increasing levels of behavioral options, which are only possible with greater cognitive complexity. A mosquito, with an ephemeral lifespan and very limited behavioral choices, would not have been shaped by natural selection to require a wide range of affective intensities.
In agreement with this, âI guess 1 mosquito-year of fully healthy life is 1.3 % as good as 1 human-year of fully healthy life, which is RPâs median welfare range of black soldier flies[1]â. I would be curious to know if you think the welfare range of mosquitoes is much smaller than 1.3 % as large as that of humans, defining welfare range as the difference between the maximum and minimum lifetime welfare per time[1].
- ^
The welfare range is smaller than the difference between the maximum and minimum instantaneous welfare per time, as the intensity of one instant can be much greater than that of a lifetime.
- ^
Thanks for sharing!
Animal welfare: DG Sante (unit G3 is responsible for Animal Welfare; unit E2 is responsible for regulatory approval policies of novel foods, including many alternative proteins) DG Agriculture (unit E3 is responsible for animal products), and DG RTD (unit B2 on bioeconomy and food systems coordinates research and innovation funding for alternative proteins), and the cabinets of associated Commissioners.
SANTE.E.4, âPesticides and biocidesâ, can relate to wild animal welfare.
Thanks, Matthew! I wonder whether something somewhat similar applies to moral uncertainty. I feel this is often used as an ad hoc justification to pursue actions which are far from optimal in terms of increasing impartial welfare, such as donating to human welfare instead of animal welfare organisations.
My anÂswers to AnÂiÂmal CharÂity EvalÂuÂaÂtorsâ quesÂtions about cost-effecÂtiveÂness analyses
Thanks for the post, Richard.
For any purpose other than an example calculation, never use a point estimate. Always do all math in terms of confidence intervals. All inputs should be ranges or probability distributions, and all outputs should be presented as confidence intervals.
I have run lots of Monte Carlo simulations, but have mostly moved away from them. I strongly endorse maximising expected welfare, so I think the final point estimate of the expected cost-effectiveness is all that matters in principle if it accounts for all the considerations. In practice, there are other inputs that matter because not all considerations will be modelled in that final estimate. However, I do not see this as an argument for modelling uncertainty per se. I see it as an argument for modelling the considerations which are currently not covered, at least informally (more implicitly), and ideally formally (more explicitly), such that the final point estimate of the expected cost-effectiveness becomes more accurate.
That being said, I believe modelling uncertainty is useful if it affects the estimation of the final expected cost-effectiveness. For example, one can estimate the expected effect size linked to a set of RCTs with inverse-variance weighting from w_1*e_1 + w_2*e_2 + ⌠+ w_n*e_n, where w_i and e_i are the weight and expected effect size of study i, and w_i = 1/ââvariance of the effect size of study iâ/â(1/ââvariance of the effect size of study 1â + 1/ââvariance of the effect size of study 2â + ⌠+ 1/ââvariance of the effect size of study nâ). In this estimation, the uncertainty (variance) of the effect sizes of the studies matters because it directly affects the expected aggregated effect size.
Holden Karnofskyâs post Why we canât take expected value estimates literally (even when theyâre unbiased) is often mentioned to point out that unbiased point estimates do not capture all information. I agree, but the clear failures of point estimates described in the post can be mitigated by adequately weighting priors, as is illustrated in the post. Applying inverse-variance weighting, the final expected cost-effectiveness is âmean of the posterior cost-effectivenessâ = âweight of the priorâ*âmean of the prior cost-effectivenessâ + âweight of the estimateâ*âmean of the estimated cost-effectivenessâ = (âmean of the prior cost-effectivenessâ/ââvariance of the prior cost-effectivenessâ + âmean of the estimated cost-effectivenessâ/ââvariance of the estimated cost-effectivenessâ)/â(1/ââvariance of the prior cost-effectivenessâ + 1/ââvariance of the estimated cost-effectivenessâ). If the estimated cost-effectiveness is way more uncertain than the prior cost-effectiveness, the prior cost-effectiveness will be weighted much more heavily, and therefore the final expected cost-effectiveness, which integrates information about the prior and estimated cost-effectiveness, will remain close to the prior cost-effectiveness.
It is still important to ensure that the final point estimate for the expected cost-effectiveness is unbiased. This requires some care in converting input distributions to point estimates, but Monte Carlo simulations requiring more than one distribution can very often be avoided. For example, if âcost-effectivenessâ = (âprobability of successâ*âyears of impact given successâ + (1 - âprobability of successâ)*âyears of impact given failureâ)*ânumber of animals that can be affectedâ*âDALYs averted per animal-year improvedâ/ââcostâ, and all these variables are independent (as usually assumed in Monte Carlo simulations for simplicity), the expected cost-effectiveness will be E(âcost-effectivenessâ) = (âprobability of successâ*E(âyears of impact given successâ) + (1 - âprobability of successâ)*E(âyears of impact given failureâ))*E(ânumber of animals that can be affectedâ)*E(âDALYs averted per animal-year improvedâ)*E(1/ââcostâ). This is because E(âconstant aâ*âdistribution Xâ + âconstant bâ) = a*E(X) + b, and E(X*Y) = E(X)*E(Y) if X and Y are independent. Note:
The input distributions should be converted to point estimates corresponding to their means.
You can make a copy of this sheet (presented here) to calculate the mean of uniform, normal, loguniform, lognormal, pareto and logistic distributions from 2 of their quantiles. For example, if âyears of impact given successâ follows a lognormal distribution with 5th and 95th percentiles of 3 and 30 years, one should set the cell B2 to 0.05, C2 to 0.95, B3 to 3, and C3 to 30, and then check E(âyears of impact given successâ) in cell C22, which is 12.1 years.
Replacing an input by its most likely value (its mode), or one which is as likely to be an underestimate as an overestimate (its median) may lead to a biased expected cost-effectiveness. For example, the median and mode of a lognormal distribution are always lower than its mean. So, if âyears of impact given successâ followed such distribution, replacing it with its most likely value, or one as likely to be too low as too high would result in underestimating the expected cost-effectiveness.
The expected cost-effectiveness is proportional to E(1/ââcostâ), which is only equal to 1/âE(âcostâ) if âcostâ is a constant, or practically equal if it is a fairly certain distribution compared to others influencing the cost-effectiveness. If âcostâ is too uncertain to be considered constant, and there is not a closed formula to determine E(1/ââcostâ) (there would be if âcostâ followed a uniform distribution), one would have to run a Monte Carlo simulation to compute E(1/ââcostâ), but it would only involve the distribution of the cost. For uniform, normal and lognormal distributions, Guesstimate would do. For other distributions, you can try Squiggle AI (I have not used it, but it seems quite useful).
Hi Joshua,
I would be happy to bet 10 k$ against short AI timelines. Note I am open to a later resolution date than the one I mention in the linked post, such that the bet is beneficial for you despite a higher risk of you not receiving the transfer in case you win.
Your post did not have any tags. I added a few.
Thanks, Laura.
Otherwise, thereâs a good risk of arriving at a directionally incorrect conclusion that can have big consequences if we act too quickly on it.
It is unclear to me whether the uncertainties you highlighted push the harm to mosquitoes as a fraction of the benefits to humans up or down. However, I very much agree there is a good risk I under or overestimated it. I did not mean to suggest AMF is harmful, as naively implied by my main estimate. As I say in the post, âit is unclear to me whether ITNs increase or decrease welfareâ. If forced to guess, I would say AMF is beneficial, but I am practically indifferent between donating to AMF and burning money. I do not see how this conclusion would qualitatively change if I had modelled the uncertainty of my inputs more explicitly with a Monte Carlo simulation. I think uncertainty in the welfare range of mosquitoes alone is enough to reach that conclusion, and probabilistic modelling would not resolve it.
I neglected the effects of ITNs on the number of wild animals because it is super unclear whether they have positive or negative lives. Yet, there is still lots of uncertainty even just in the effects I considered. RPâs 5th and 95th percentile welfare ranges of black soldier flies are 0 and 15.1 (= 0.196/â0.013) times their median. This suggests that, even ignoring effects on the number of wild animals, and just accounting for uncertainty in mosquitoesâ capacity for welfare, the 5th and 95th percentile harm to mosquitoes caused by ITNs are 0 and 11.5 k (= 15.1*763) times their benefits to humans. So it is unclear to me whether ITNs increase or decrease welfare.
More importantly, I think the large uncertainty should update one towards learning more, and supporting more robustly beneficial interventions. In particular, donating less to organisations like AMF, whose cost-effectiveness may well be majorly driven by unclear effects on animals, and more to ones like Arthropoda Foundation, SWP, and WAI. Do you agree?
Thanjs, NuĂąo.
I think it is both an objective fact of life, and also a factor that varies across people. For example, for valuations of human welfare as a function of e.g. country of birth, there are objective biological differences between humans born in different countries (which I think have a negligible impact on their capacity for welfare), and also different levels of nationalism.