You might be surprised to learn that CEAs of mental health interventions in the EA space (example) don’t count the value of preventing suicide and self-harm. But on a DALY basis, self-harm and suicide have roughly the same burden in total as depression as a whole, precisely because they’re so much worse (this is to say nothing of effects on income).

I think that mental health interventions, and especially direct suicide counselling, might be really underrated, simply because the research hasn’t been done in a lot of depth (that I’m aware of). Part of this is because it’s quite hard to accurately quantify the effects of interventions on long-term suicide rates (you need many years, and access to death records). However, there are a few good studies that I think might point to ways this could at least be estimated, and then we can agree on an appropriate evidence discount.

The theory of change gets quite convoluted. For example, people may report feeling suicidal or having suicidal thoughts, but this may have no real correlation with their attempts. Or we may find that people who report feeling less suicidal commit suicide less often, but it may not be true that reducing their feelings of suicidality actually has any effect on their long-term attempt rate.

Here’s a good paper looking at 84,000 people’s PHQ-9 scores and follow-ups with suicidality. Unfortunately, the evidence isn’t causal, but this study looks at suicide prevention RCTs and finds that, at least, depression interventions reduce ideation, but not suicidality. I’ll be doing a bit more research in this area because I think it’s quite promising!

A new study in The Lancet estimates that high USAID spending saved over 91 million lives in the past 21 years, and that the cuts will kill 14 million by 2030. They estimate high USAID spending reduced all-cause mortality by 15%, and by 32% in under 5s.

How are you thinking about trade as a deterrent? The typical defence here brings up TSMC—but IMHO should also bring up Foxconn, a gigantic employer in China—and that if the Chinese consumer economy collapses, this could cause enough headaches to make an attack unreasonable.

In this case, the two main courses of action would look like:

1. Use policy and lobbying within the US to reduce tariffs and chip controls (neglected on the margins, ex. chip controls, but probably not broadly)
2. Find other means of increasing consumer spending on foreign goods within China (seems not neglected as corporations have a direct incentive to pursue it)

I haven’t used it extensively for research tasks yet, but I do really worry about that. There is something I feel viscerally when I ‘get’ a paper that often requires a deep look into the mechanics of how a study was run (i.e. reading the whole thing), that’s just not going to come from a skim-read. There’s lots of nuance in the literature my intervention is based off of, that if I didn’t understand, would lead me to inappropriately embellish my results.

I think if I was using research tools, they’d save me a lot of time in the googling phase, but then I’d still skim papers for value, and hand-read the most important ones. Anecdotally, this seems to be what most full-time researchers do.

(I also find talking confidently about the details of papers impresses people I talk to, which can be valuable in and of itself)

How robust is your assumption about the value life events staying constant? If it were not true, then there may not be any rescaling to explain. Intuitively, if wellbeing saturates at the top end, having a really positive thing happen to me genuinely might not move the needle as much. In other words, if my life is already a 9, is it realistic to expect getting married will take me to a 10—a perfect life?

HLI have a good, but very preliminary, look at the linearity/compression of wellbeing here, and it seems like linearity/compression is actually very under-studied. This seems odd to me, considering that it would probably dramatically shift where you allocate resources if linearity was true vs if there were bigger gains to be made in the middle of the spectrum.

(Apologies if you have addressed this somewhere)

All of the headlines are trying to run with the narrative that this is due to Trump pressure, but I can’t see a clear mechanism for this. Does anyone have a good read on why he’s changed his mind? (Recent events feel like: Buffet moving his money to his kids’ foundations & retiring from BH, divorce)

I liked Bob Jacob’s essay Is Effective Altruism neocolonial?.

Aid dependency is a really interesting problem, where charities can become victims of their own success. I think we should be very thoughtful about counterfactual government funding—even when, due to natural government inefficiencies, it might be less cost-effective.

One place I think EAs can do a lot of good is in charity entrepreneurship. There are often good emerging ideas that need a strong evidence base before governments will adopt them, but a shortage of ambitious people willing to take these risks. At Kaya Guides, we see our role as pioneering a novel treatment method, and then working with governments to implement. Even if we don’t do this ourselves, our counterfactual impact will always have been to create an evidence base that encourages others to do so!

Thanks for the feedback! I’m not really smart enough to figure something like that out tbh, and by the point I’d seen that my realistic options were within an order of magnitude of each other (and both high-risk with high overlap) I was pretty satisfied that my decision was likely gonna hinge on something else.

Maybe your adjustment would take it outside that range but I think at the point of extreme success these charities would be selling impact at competitive rates (so funders would be getting marginal value out of them), and more than likely going to counterfactual funders (ex. government). Maybe this is truer in GHD and especially mental health than in animal welfare, which seems more concentrated. But yeah, at this point I was pretty satisfied that Kaya Guides had minimal risk of substantial funding displacement in a success scenario (I can’t be too specific about this in public), so I picked it.

(Maybe again—I’m just highlighting my specific scenario, there’s definitely an attempt to generalise here but I didn’t think too hard through it)

No, but I think that’s reasonable in most cases (although hard to figure out exactly how to allocate it).

I didn’t. It evidently works—as do cooperatives, which I was also excited to found—but I think the big worry is up the top end. It’s very hard to imagine a FAANG company structured this way. And some of the average-case calculations above are skewed upwards by a handful of top success stories.