Yep, and that's about 5x existing GiveWell top charities. Also, GiveWell has made a 700k grant to Resolve to Save Lives (RTSL) for their salt reduction work in China; CEARCH previously recommended and evaluated RTSL for their salt policy work in Southeast & South Asia, and I'm very excited to see GiveWell make this exploratory grant.

Let's discuss this at length!

The tractability on this will be terrible - you'll be trying to persuade poor countries to limit quality/quantity/variety of food availability to their own people, and you can imagine how that will go. Additionally, there may be potential human costs in terms of nutrition and economic growth.

If you do want to affect AW in LMICs, Innovate Animal Agriculture style work trying to affect the kind of industrial animal agriculture seems far more tractable (in fact it's probably more tractable than in HICs, since e.g. there are no sunk costs in terms of equipment and capital).

Hi Vasco,

We have standard GCR discounts when estimating long term impact, but for AI - we're generally more sceptical, both on paperclipping and on extremely rosy projections of economic growth. In any case, while there might be a theoretical case for discounting income-based interventions (if you really believe GDP growth is going jump to 10% per annum, we're obviously moving up the DMR curve more rapidly), there's much less direct impact on health (in fact, if you think income is going to drastically increase, that makes consumption greater, and the DALY burden of diseases of affluence much worse, and hence preventing them more cost-effective).

The percentage of EAs earning to give is too low

Money is the major bottleneck for high impact charities, at least in GHD and AW (and some GCR causes). Meanwhile, there's an excess in demand for EA jobs relative to the supply (everyone knows it's extremely competitive). Hence, the marginal value of getting more money in via earning to give (loosely defined - not everyone needs to be in finance or tech) is probably higher than trying to squeeze into a direct role where replaceability is extremely high.

This isn't even an EA vs non-EA thing. I assure you that randomly touching women, whether female colleagues or strangers, in a normal corporate or government or non-profit job will deservedly get you fired for sexual harrassment.

You may wish to talk to Health Progress Hub.

It's true that there are diminishing marginal returns, and with less funding and fewer projects/people around, there is now a bunch of opportunities for impact which you can exploit (where previously someone else would have done it anyway).

However, there's also a countervailing reduction in marginal value of labour due to reduced availability of capital and non-labour input, especially since cuts aren't necessarily well targeted (e.g. keeping staff while capital investment is slashed). Loss of infrastructure field-wide is also a critical problem (e.g. all those interventions and programmes piggybacking on AIDS clinics)

Hi Vasco,

It would be hard to say without diving deeper into the literature - the way we did it was to look at the number of diabetes DALYs that is causally attributable to SSB consumption, and then just taking consumption and the DALY burden to vary linearly.

The virtue of this approach is its greater simplicity, particularly because it's complicated to get from higher mortality risk to DALY (you have to do a bunch of additional calculations and transformations to get from relative risk and baseline rates and average years of life remaining to years of life loss, and failure to disaggregate into age and sex specific stuff at each stage introduces issues iirc), so might as well just do the population-level analysis.