CEO @ Open Philanthropy
1101 karmaJoined Nov 2014


Exciting news! I worked closely with Zach at Open Phil before he left to be interim CEO of EV US, and was sad to lose him, but I was happy for EV at the time, and I'm excited now for what Zach will be able to do at the helm of CEA.

Great to hear about finding such a good fit, thanks for sharing!

Hi Dustin :)

FWIW I also don't particularly understand the normative appeal of democratizing funding within the EA community. It seems to me like the common normative basis for democracy would tend to argue for democratizing control of resources in a much broader way, rather than within the self-selected EA community. I think epistemic/efficiency arguments for empowering more decision-makers within EA are generally more persuasive, but wouldn't necessarily look like "democracy" per se and might look more like more regranting, forecasting tournaments, etc.

Just wanted to say that I thought this post was very interesting and I was grateful to read it.

Just wanted to comment to say I thought this was very well done, nice work! I agree with Charles that replication work like this seems valuable and under-supplied.

I enjoyed the book and recommend it to others!

In case of of interest to EA forum folks, I wrote a long tweet thread with more substance on what I learned from it and remaining questions I have here: https://twitter.com/albrgr/status/1559570635390562305

Thanks MHR. I agree that one shouldn't need to insist on statistical significance, but if GiveWell thinks that the actual expected effect is ~12% of the MK result, then I think if you're updating on a similarly-to-MK-powered trial, you're almost to the point of updating on a coinflip because of how underpowered you are to detect the expected effect.

I agree it would be useful to do this in a more formal bayesian framework which accurately characterizes the GW priors. It wouldn't surprise me if one of the conclusions was that I'm misinterpreting GiveWell's current views, or that it's hard to articulate a formal prior that gets you from the MK results to GiveWell's current views.

Thanks, appreciate it! I sympathize with this for some definition of low FWIW: "I have an intuition that low VSLs are a problem and we shouldn't respect them" but I think it's just a question of what the relevant "low" is.

Thanks Karthik. I think we might be talking past each other a bit, but replying in order on your first four replies:

  1. My key issue with higher etas isn't philosophical disagreement, it's as guidance for practical decision-making. If I had taken your post at face value and used eta=1.5 to value UK GDP relative to other ways we could spend money, I think I would have predictably destroyed a lot of value for the global poor by failing to account for the full set of spillovers (because I think doing so is somewhere between very difficult and impossible). Even within low-income countries there are still pervasive tax, pecuniary, other externalities from high-income spending/consumption on lower-income co-nationals, that are closer to linear than logarithmic in $s. None of this is to deny the possibility or likelihood that in a totally abstract pure notion of consumption where it didn't have any externalities at all and it was truly final personal consumption, it would be appropriate to have a log or steeper eta, it's to say that that is a predictably bad approximation of our world and accordingly a bad decision rule given the actual data that we have. I think the main reply here has to be a defense of the feasibility of explicitly accounting for all relevant spillovers, and having made multiple (admittedly weak!) stabs in that direction, I'm personally pessimistic, but I'd certainly love to see others' attempts.
  2. In the blog post I linked in my #2 above we explicitly consider the set point implied by the IDInsight survey data, and we think it's consistent with what we're doing. We're open to the argument for using a higher fixed constant on being alive, but instead of making you focus more on redistribution of income, the first order consequence of that decision would be to focus more on saving poor people's lives (which is in fact what we predominantly do). It's also worth noting that as your weight there gets high, it gets increasingly out of line with people's revealed preferences and the VSL literature (and it's not obvious to me why you'd take those revealed preferences less seriously than the revealed preferences around eta).
  3. "I think almost everyone would agree that 10% income increase is worth much more to a poor person than a rich person" - I don't think that's right as a descriptive claim but again even if it were the point I'm making in #1 above still holds - if your income measure is imperfect as a measure of purely private consumption without any externalities, and I think they all are, then any small positive externalities that are ~linear in $ will dominate the effective utility calculation as eta gets to or above 1. I think there are many such externalities - taxes, philanthropy, aid, R&D, trade... - such that very high etas will lead to predictably bad policy advice.
  4. You can add a constant normalizing function and it doesn't change my original point - maybe it's worth checking the Weitzman paper I linked to get an intuition? There's genuinely more "at stake" in higher incomes when you have a lower eta vs a higher eta, and so if you're trying make the correct utilitarian decision under true uncertainty, you don't want to take a unweighted mean of eta and then run with it, you want to run your scenarios over different etas and weight by the stakes to get the best aggregate outcome. (I think how you specify the units might matter for the conclusion here though, a la the two envelope problem; I'm not sure.)
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