"At a certain point, we just have to trust the peer-review process"

Coming here late, found it an interesting comment overall, but just thought I'd say something re interpreting the peer reviewed literature as an academic, as I think people often misunderstand what peer review does. It's pretty weak and you don't just trust what comes out! Instead, look for consistent results being produced by at least a few independent groups, without there being contradictory research (researchers will rarely publish replications of results, but if a set of results don't corroborate a single plausible theoretical picture, then something is iffy). (Note it can happen for whole communities of researchers to go down the wrong path, though - it's just less likely than for an individual study.) Also, talk to people in the field about it! So there are fairly low cost ways to make better judgements than believing what one researcher tells you. The scientific fraud cases that I know involved results from just one researcher or group, and sensible people would have had a fair degree of scepticism without future corroboration. Just in case anyone reading this is ever in the position of deciding whether to allocate significant funding based on published research.

"Science relies on trust, so it's relatively vulnerable to intentionally bad, deceptive actors"

I don't think science does rely on trust particularly highly, as you can have research groups corroborating or casting doubt on others' research. "Relatively" compared to what? I don't see why it would be more vulnerable to be actors than most other things humans do.

A very interesting summary, thanks.

However I'd like to echo Richard Chappell's unease at the praising of the use of short-term contracts in the report. These likely cause a lot of mental health problems and will dissuade people who might have a lot to contribute but can't cope with worrying about whether they will need to find a new job or even career in a couple of years' time. It could be read as a way of avoiding dealing with university processes for firing people - but then the lesson for future organisations may be to set up outside a university structure, and have a sensible degree of job security.

Thanks, it's good to know it's had input from multiple knowledgable people. I agree that this looks like a good thing even if it's implemented imperfectly!

Thanks for putting together the doc.

For the suggested responses, are they informed by expertise or based on a personal view? This would be useful to know where I'm not sure about them. E.g. for the question on including images, I wondered if they could be misleading if they show animals (as disease and other health problems aren't very visible, perhaps leading people to erroneously think "those animals look OK to me" or similar).

I also wonder if there's a risk from this that products get labelled as "high" welfare when the animals still suffer overall, reducing impetus for further reform. I think the scheme would still be good, but I wonder if there's scope to add an argument that labels like "high" should be reserved only for cases where welfare is independently assessed to indeed be probably positive and high.

the second most upvoted comment (27 karma right now) takes me to task for saying that "most experts are deeply skeptical of Ord’s claim"  (1/30 existential biorisk in the next 100 years).

I take that to be uncontroversial. Would you be willing to say so?

I asked because I'm interested - what makes you think most experts don't think biorisk is such a big threat, beyond a couple of papers?

I guess it depends on what the "correct direction" is thought to be. From the reasoning quoted in my first post, it could be the case that as the study result becomes larger the posterior expectation should actually reduce. It's not inconceivable that as we saw the estimate go to infinity, we should start reasoning that the study is so ridiculous as to be uninformative and so not the posterior update becomes smaller. But I don't know. What you say seems to suggest that Bayesian reasoning could only do that for rather specific choices of likelihood functions, which is interesting.

It's a potential solution, but I think it requires the prior to decrease quickly enough with increasing cost effectiveness, and this isn't guaranteed. So I'm wondering is there any analysis to show that the methods being used are actually robust to this problem e.g. exploring sensitivity to how answers would look if the deworming RCT results had been higher or lower and that they change sensibly? 

A document that looks to give more info on the method used for deworming looks to be here, so perhaps that can be built on - but from a quick look it doesn't seem to say exactly what shape is being used for the priors in all cases, though they look quite Gaussian from the plots.

Hmm it's not very clear to me that it would be effective at addressing the problem - it seems a bit abstract as described. And addressing Pascal's mugging issues seems like it potentially requires modifying how cost effectiveness estimates are done ie modifying one component of the "cluster" rather than it just being a cluster vs sequence thinking matter. It would be good to hear more about how this kind of thinking is influencing decisions about giving grants in actual cases like deworming if it is being used.

Something I've wondered is whether GiveWell has looked at whether its methods are robust against "Pascal's mugging" type situations, where a very high estimate of expected value of an intervention leads to it being chosen even when it seems very implausible a priori. The deworming case seems to fit this mould to me somewhat - an RCT finding a high expected impact despite no clear large near term health benefits and no reason to think there's another mechanism to getting income improvements (as I understand it) does seem a bit like the hypothetical mugger promising to give a high reward despite limited reason to expect it to be true (though not as extreme as in the philosophical thought experiments).

Actually, doing a bit of searching turned up that Pascal's mugging has been discussed in an old 2011 post on the GiveWell blog here, but only abstractly and not in the context of any real decisions. The post seems to argue that past some point, based on Bayesian reasoning, "the greater [the 'explicit expected-value' estimate] is, the lower the expected value of Action A". So by that logic, it's potentially the case that had the deworming RCT turned up a higher, even harder to believe estimate of the effect on income, a good evaluation could have given a lower estimate of expected value. Discounting the RCT expected value by a constant factor that is independent of the RCT result doesn't capture this. (But I've not gone through the maths of the post to tell how general the result is.)

The post goes on to say 'The point at which a threat or proposal starts to be called “Pascal’s Mugging” can be thought of as the point at which the claimed value of Action A is wildly outside the prior set by life experience (which may cause the feeling that common sense is being violated)'. Maybe it's not common sense being violated in the case of deworming, but it does seem quite hard to think of a good explanation for the results (for an amateur reader like me anyway). Has any analysis been done on whether the deworming trial results should be considered past this point? It seems to me that that would require coming up with a prior estimate and checking that the posterior expectation does behave sensibly as hypothetical RCT results go beyond what seems plausible a priori. Of course, thinking may have evolved a lot since that post, but it seems to pick up on some key points to me.

It looks like >$10M were given by GiveWell to deworming programs in 2023, and from what I can tell it looks like a large proportion of funds given to the "All Grants" fund went to this cause area, so it does seem quite important to get the reasoning here correct. Since learning about the issues with the deworming studies, I've wondered whether donations to this cause can currently make sense - as an academic, my life experience tells me not to take big actions based on results from individual published studies! And this acts as a barrier to feeling comfortable with donating to the "All Grants" fund for me, even though I'd like to handover more of the decision-making to GiveWell otherwise.

What good solutions are there for EAs leaving money to charity in wills, in terms of getting them legally correct but not incurring large costs?

I've found this 2014 forum post that looks to have good info but many of the links no longer work - for example, it has a broken link to a form for getting a free will - does a resource like that still exist somewhere?

There's also the GWWC bequests page. When I tried their "tool", it directed me to an organisation called FareWill - has anyone used them and found it to give a good result?

I get the impression that the low-cost will services out there are based on templates for leaving assets to family and friends and aren't so well suited to having charities as the main beneficiaries - in particular, including clauses for what to do if the charities no longer exist and some broader instruction needs to be given (I tried freewills.co.uk, but it didn't produce something suitable). Has anyone found a will-writing service that worked well at a reasonable cost? Or is using a solicitor the recommended way in these cases, and am I wrong to think that would cost hundreds of pounds? [Edit to add - I live in England, so info relevant for there is particularly welcome.]

Edit to add some keywords for searching, as someone pointed out to me that searching for "will" brings up lots of other things!: testament, writing will, leave money to charity.