Makes sense, thanks!

Why is it generally better for individuals to donate to 501(c)(4) organizations than to (c)(3)'s? I'm deeply ignorant in this space, so it's a genuine question.

My super naive read is that c3's are tax deductible (which is nice), presumably you think there is more than a 50% bonus in effectiveness of c4's?

I don't think that the intuition behind 'curve fitting' will actually get you the properties you want, at least for the formalizations I can think of.

How would you smooth out a curve that contains the St. Petersburg paradox? Simply saying to take the average of normal intuition and expected-value calculus (which you refer to as fanaticism) doesn't help. EV calculus is claiming an infinity. I'm not aware of curve fitting approaches that give understandable curves when you mix infinite & finite values.

Plus, again, what dimensions are you even smoothing over?

I don't get how you're actually proposing doing curve-fitting. Like, the axes on your chart seem fake, particularly 'moral cases'. What does 2 vs 8 'moral cases' mean? What is a concrete example of a decision where you do X without curve fitting, but Y with curve fitting?

Without an actual mathematical formalization or examples, I struggle to see what your proposal looks like in practice. This seems like another downside relative to threshold deontology, where it is comparatively intuitive to see what happens before and after the threshold.

I don't think that the study you cited here supports a 52% reduction in diarrhoea risk for these wells. The 52% quote is:

Compared with an unimproved source, provision of an improved drinking water supply on premises with higher water quality reduced diarrhoea risk by 52% (n=2; 0·48 [0·26–0·87])

The wells created by Wells4Wellness do not deliver water to people's homes, as far as I can tell. Doing so would be substantially more expensive. That study also seems to only consider water to be 'improved' if it is chlorinated, filtered, or solar treated. Searching for 'well' in that paper does not yield any hits. I could not find strong studies comparing deep well water to chlorinated water.

I think this is an interesting exercise, and it's good to see more analyses of policy. But I don't see this as an argument for the title 'EAs should do more rough policy modeling'.

A post really interacting with that title would be showing how rough policy modeling is useful (ie, showing how it gets picked up by governments in actual policy, or has other positive downstream effects). Ideally, we'd get into how whether 'rough policy modeling' is more useful than than other similarly difficult activities EAs might do.

Best of luck! As someone who doesn't eat eggs, I half-jokingly tell folks I can tell when cookies are vegan because they are bad. I look forward to not being able to use that heuristic!

GiveWell

For EA folks in tech, I'm still giving mock interviews. I'm bumping this into quick takes because my post is several years old, and I don't advertise it well.

There are a lot of 'lurkers', but less than 30 folks would be involved in the yearly holiday matching thread and sheet. Every self-professed EA I talked to at Google was involved in those campaigns, so I think that covers the most involved US Googlers.

Most people donated closer to 5-10% than Jeff or Oliver's much higher amounts, that is for sure true.

So I think both your explanations are true. There are not that many EAs at Google (although I don't think that's surprising), and most donate much less than they likely could. I put myself in that bucket, as I donated around 20%, but likely could have done close to twice that. Although it would be hard for me to do that in recent years, as I switched to Waymo where I can't sell my stock.