I am a generalist quantitative researcher. I am open to volunteering and paid work. I welcome suggestions for posts. You can give me feedback here (anonymously or not).
Vasco Grilošø
Karma: 12,037
Hi Ariel. You may be interested in Brian Tomasikās post Dissolving Confusion about Consciousness.
It doesnāt make sense to ask questions like, Does a computer program of a mind really instantiate consciousness? That question reifies consciousness as a thing that may or may not be produced by a program. Rather, the particles constituting the computer just moveāand thatās it. The question of whether a given physical operation is āconsciousā is not a factual dispute but a definitional one: Do we want to define consciousness as including those sorts of physical operations?
Relatedly, you may like this linkpost for Ethics without sentience. Facing up to the probable insignificance of phenomenal consciousness by FranƧois Kammerer.
The relevant question is how much animalsā experiences are discounted relative to the global poorās experiences. If theyāre discounted the same amount, animal welfare remains ~1000x as cost-effective [ratio between the cost-effectiveness of corporate campaigns for broiler welfare and GiveWellās top charities neglecting effects on non-target individuals].
I got this estimate based on the sentience-adjusted welfare ranges Rethink Priorities (RP) initially presented, and neglecting effects on soil invertebrates. However, I have little idea about whether chicken welfare reforms increase or decrease welfare accounting for uncertainty in welfare comparisons across species, and effects on soil invertebrates. For the sentience-adjusted welfare ranges presented in Bob Fischerās book, which are similar to the ones RP initially presented, I think effects on soil invertebrates would be much larger than those on chickens. So, trusting the values in the book, and excluding interventions decreasing uncertainty, I would focus on increasing the welfare of soil invertebrates by increasing or decreasing agricultural land. I believe this can be achieved more cost-effectively by the Good Food Institute (GFI) or Giving What We Can (GWWC) than interventions improving the conditions of farmed animals. In reality, I favour interventions decreasing uncertainty about welfare comparisons across species, and effects on soil invertebrates.
Hello. You may be interested in David Thorstadās series Instrumental convergence and power seeking.
I see. I wonder if any of the patients who has benefitted from DMT would be interested in appearing on podcasts. I suspect founders of orgs fighting cluster headaches, people leading the research, and people with cluster headaches who have personally benefitted would more easily be accepted as guests than someone hired for public-facing work who is not leading the research, and has not personally beneffited.
Hello Jim. I had understood you used data from GiveWell (this is mentioned in the section I linked above with your methodology). However, as far as I know, GiveWell has never said the cost-effectiveness of their marginal spending in 2025 matched the cost-effectiveness of all their grants considered together in 2025, which is what you are assuming (see the quote after my question in the comment above). Here is what they say in the post you linked.
In 2025, we generally considered funding opportunities that our research estimated to be at least 8x our cost-effectiveness benchmark. Overall, we estimate that the average cost-effectiveness of the money spent across all our grants was approximately double that: 16x our benchmark.
So GiveWell estimates the cost-effectiveness of all their grants considered together in 2025 was 16 times their benchmark. The cost-effectiveness of GiveWellās marginal spending in 2025 was lower than this. GiveWell prioritises the most cost-effective grants, and some grants had a cost-effectiveness lower than 16 times their benchmark.
The marginal cost-effectiveness of GiveWellās marginal spending in 2025 may have exceeded their bar. In principle, it could have been anything from 8 to 16 times their benchmark. In practice, I think it is close to 8 times their benchmark. Assuming they funded all grants with a cost-effectiveness higher than their bar of 8 times their benchark (considering all factors, not just the ones covered in the explicit cost-effectiveness analysis (CEA)), GiveWell granting more in 2025 would not have led to more grants with a cost-effectiveness higher than 8 times their benchmark (which would have been made anyway). It would have led to grants with a cost-effectiveness of around 8 times their benchmark (slightly below or above 8 times their benchmark because the distribution of the cost-effectiveness of the grants is not perfectly continuous).
Hi Brenton.
Salary
Opportunity cost
Best quantified from the point of view of aligned funding: roughly, how much an aligned funder would be willing to pay for the impact they expect this person could produce if they werenāt working at their current org.
Capacity-building value
Working at the organisation affects the expected value of the rest of that staff memberās career: they gain skills and context, and based on their experience there, the job increases/ādecreases their inclination to remain in the ecosystem.[1]
Should the opportunity cost as defined above already cover capacity-building value? Funders should account for capacity-building value when assessing how much they would be willing to pay for the impact of hiring someone.
Hi Toby. Great post.
Hello Alfredo. Thanks for this update. I am glad you have many ideas to make progress.
Our project ClusterInfo is one of our attempts to reach such patients. Itās a website with free resources on how to diagnose and treat cluster headaches, currently available in eight languages. Since launching in late May, weāve already reached over 11,000 unique visitors, and weāre thinking hard about how to make sure that anyone, anywhere searching for information on cluster headaches can quickly find the information they need. We work with patients, clinicians, and other advocates to ensure the content is accurate, comprehensive, and easy to understand. You can find some web analytics here, in case youāre curious.
Have you considered trying to spread the word about ClusterInfo on podcasts? Claude says Joe Rogan has had at least 3 episodes centred on DMT:
Rick Strassman, #1854 (August 2022). Strassman is the psychiatrist who ran the 1990s University of New Mexico DMT trials. He wrote āDMT: The Spirit Moleculeā, a book about his findings and experiences researching DMT, and Rogan hosted the documentary version of it. sportskeeda
Rick Strassman again, #2385 (26 September 2025). He discussed his 1990s DMT studies, and the two compared DMT experiences with ancient religious texts, especially the Hebrew Bible and the Book of Enoch. He also promoted a new book, which another summary describes as being about trauma, psychedelics and spiritual growth. shortformpodwise
Andrew Gallimore, #2403 (30 October 2025). Gallimore is a chemical pharmacologist and neurobiologist. The interview was on DMT and the nature of reality. It covered his book, subtitled āConfronting the mystery of the worldās strangest drugā. singjupost
Hi Siebe. Nice point. Relatedly, I think people often overestimate the importance of the probability of sentience (in the EA community too).
If you trust there is as little variation in the probability of sentience as suggested by the values used by Ambitious Impact (AIM) and Animal Charity Evaluators (ACE), or presented in Bob Fischerās book about comparing welfare across species, I believe there are other factors which may be more important for the probability of a small donation increasing animal welfare:
Donating to incremental instead of hits-based interventions.
Donating to smaller organisations.
Donating to organisations in lower income countries
I wonder to what extent people donate to interventions targeting animals which are more likely to be sentient to boost the probability of increasing welfare. People routinely take actions which are super unlikely to actually matter:
I calculate driving a car for 10 km in Great Britain without a seatbelt leads to 1 additional death with a probability of 1 in 73.0 M. AIM uses a probability of sentience of shrimps which is 34.2 M times as high.
Andrew Gelman found the probability of a voter in a small United States (US) state polling around 50ā50 in a close election nationally changing the outcome of the national election could get as high as 1 in 3 million. AIM uses a probability of sentience of shrimps which is 1.40 M times as high.
Hi Henning and Tom. Nice post.
How moral weights and soil life change cause prioritisation
It accounts for key variables at play in determining and comparing the cost-effectiveness of different interventions, including:
How to weigh the welfare of humans against that of non-human animals and that of different non-human animals between themselves (moral weights)
How to weigh different time periods, like the near future (0-5 years) versus the very distant future (over 500 years), e.g., in light of deep uncertainty about far future effects (Discount factors across time periods)
Attitudes towards risk
Diminishing returns
The first attempt to include the possibility of AI transforming the world so radically that any interventions not aimed at altering the trajectory of AI would be rendered ineffective (under improvement)
@Laura Muresianu and @Jim Buhler, on diminishing returns, why do you set the (marginal) cost-effectiveness of funding GiveWellās All Grants Fund to the cost-effectiveness of the grants GiveWell made in 2025 instead of GiveWellās cost-effectiveness bar?
We used this information [about the grants GiveWell made in 2025] to construct a distribution for the average cost-effectiveness of GiveWellās entire portfolio of spending in 2025 in Python, which weāll assume is roughly equal to the marginal cost-effectiveness of GiveWell spending.
I think GiveWellās current cost-effectiveness bar is 6 times their benchmark. From the page I just linked which was last updated in September:
As of May 2026, our bar for funding programs is 6x our benchmark
You assumed a significantly higher cost-effectiveness.
Hi Dan. I expect terrorist attacks to be super unlikely to cause human extinction in the absence of very strong evidence suggesting otherwise. For the attacks killing more than 10 people among the 202 k listed on the Global Terrorism Database (GTB), the fraction killing more than 10*N people is around 1 % of the fraction killing more than N people. This suggests a Pareto distribution with a tail index of 2. Around 0.001 % of attacks killed more than 1 k people. Assuming the same Pareto distribution (straight line fitted to the section of the graph below with more than 10 deaths), more than 1 billion deaths would be 10^-12 (= 0.01^(9 ā 3)) times as likely as more than 1 k deaths. So the Pareto distribution implies only 10^-17 (= 10^(-5 ā 12)) of terrorist attacks cause more than 1 billion deaths. I think the actual risk is way higher. At the same time, I believe a significant risk of a terrorist attack causing human extinction, like 1 % over the next 20 years, would depart a lot from the most natural uninformed ways of extrapolating past data. A pandemic causing human extinction looks much more plausible based on past data (although I still guess the risk of human extinction in the next 20 years is much lower than 1 %).
Hi Marcus and Jim. Great post. I agree. I also liked the direct writing style.
Hi Liam. Nice post. You may be interested in this linkpost for the article āThe Conscious Nematode: Exploring Hallmarks of Minimal Phenomenal Consciousness in Caenorhabditis Elegansā.
And given the sheer number of soil nematodes ā some researchers estimate there may be over 10^20 of them, or more than a million million million nematodes! ā that means their aggregate welfare could be extremely large, possibly larger than all other animals on Earth.
In this post, āwelfare range as a fraction of that of humansā means āindividual welfare per fully-healthy-animal-year as a fraction of the welfare per fully-healthy-human-yearā.
Why AI-asĀsisted bioweapons from lone wolves and non-state acĀtors wonāt kill us all
I donāt think you can extrapolate standard population models past the invention of artificial wombs and robo-nannies. The āRecoveryā premise is much more plausible if creating new lives is less personally costly.
Why would artificial wombs and robo-nannies have very different effects from other innovations that have decreased the time cost of having children (for example, washing machines), or increased the income of prospective parents (for example, increasing income of women)? A lower cost of having children as a fraction of available income would increase fertility if the cost of everything else remained the same, but alternatives would become cheaper too relative to available income. It is unclear to me whether your point strengthens or weakens the conclusions of Alexandrie and Eden (2025) under the population models they analysed.
That makes sense.
Hi Mal.
Drone replacements for pollination services. Bring down the cost of micro-drones that can pollinate almond trees down to be cost-competitive with bee-based pollination services, potentially ending an industry that harms billions of bees each year.
Are you assuming the bees would prefer not existing? I suppose this is very uncertain.
GiveWell says āWe maintain a cost-effectiveness threshold [bar] at a level where we expect to be able to fully fund all the opportunities we find above itā, as I have been assuming. So I am confident it would be better to set the marginal cost-effectiveness of GiveWellās All Grants Fund (AGF) to GiveWellās bar, 6 times their benchmark in May 2026, instead of the cost-effectiveness of all the grants they made in a year.
You are currently assuming AGF has a marginal cost-effectiveness of around 16 times GiveWellās benchmark (see my 1st comment in this thread), 2.67 (= 16ā6) times GiveWellās bar in May 2026. This is a significant difference in the context of global health interventions, whose cost-effectiveness is less uncertain compared to that of interventions targeting animals, and decreasing catastrophic risks neglecting effects on non-target individuals. So I suggest you update your assumption about the marginal cost-effectiveness of AGF before CCF makes more grants.
I am considering publishing a post about this on October 28. Let me know if you update your assumptions.