Owen_Cotton-Barratt comments on Charity Evaluators: first model and open questions (Oxford Prioritisation Project) - Effective Altruism Forum

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Comment author: Owen_Cotton-Barratt 25 April 2017 02:59:15PM 4 points [-]

The fact that sometimes people's estimates of impact are subsequently revised down by several orders of magnitude seems like strong evidence against evidence being normally distributed around the truth. I expect that if anything it is broader than lognormally distributed. I also think that extra pieces of evidence are likely to be somewhat correlated in their error, although it's not obvious how best to model that.

Comment author: RyanCarey 25 April 2017 06:19:18PM 3 points [-]

I expect that if anything it is broader than lognormally distributed.

It might depend what we're using the model for.

In general, it does seem reasonable that direct (expected) net impact of interventions should be broader than lognormal, as Carl argued in 2011. On the other hand, it seems like the expected net impact all things considered shouldn't be broader than lognormal. For one argument, most charities probably funge against each other by at least 1/10^6. For another, you can imagine that funding global health improves the quality of research a bit, which does a bit of the work that you'd have wanted done by funding a research charity. These kinds of indirect effects are hard to map. Maybe people should think more about them.

AFAICT, the basic thing for a post like this one to get right is to compare apples with apples. Tom is trying to evaluate various charities, of which some are evaluators. If he's evaluating the other charities on direct estimates, and is not smoothing the results over by assuming indirect effects, then he should use a broader than lognormal assumption for the evaluators too (and they will be competitive). If he's taking into account that each of the other charities will indirectly support the cause of one another (or at least the best ones will), then he should assume the same for the charity evaluators.

I could be wrong about some of this. A couple of final remarks: it gets more confusing if you think lots of charities have negative value e.g. because of the value of technological progress. Also, all of this makes me think that if you're so convinced that flow-through effects cause many charities to have astronomical benefits, perhaps you ought to be studying these effects intensely and directly, although that admittedly does seem counterintuitive to me, compared with working on problems of known astronomical importance directly.

Comment author: Owen_Cotton-Barratt 26 April 2017 11:45:34AM 1 point [-]

I largely agree with these considerations about the distribution of net impact of interventions (although with some possible disagreements, e.g. I think negative funging is also possible).

However, I actually wasn't trying to comment on this at all! I was talking about the distribution of people's estimates of impact around the true impact for a given intervention. Sorry for not being clearer :/