I did a sort of version of this for many years. Eventually it became a huge amount of somewhat painful work and it was never exactly clear to me how many people it was helping; it got a lot of karma, but so did a lot of much lower effort posts, and I didn't have a lot of other feedback mechanisms.

Quick things:
1. The vast majority of the funding comes from a very few funders. In the cases of GiveWell/ACE, they are meant more for many smaller donors. Historically, funding was not the main bottleneck in longtermism ("we might as well fund everything") - that said, this is changing now, so it could be a good time to do something different.
2. My guess is that few strong people wanted to themselves make a new evaluator in this space. Many of the strong people who could evaluate longtermist orgs seem to prefer working at OP or, more likely, just working in the field directly. EA is kind of a "do-ocracy" - often the reason for "why didn't this happen?" is, "it would require some strong talent, and none really was excited about this."
3. Similar to (1), I haven't seen a large funding base be very interested in spending money on evaluation here. 
4. Much of the longtermist field is fairly friendly with one another and I think there's a gap of candid evaluation. 
5. Honestly, I think a lot of opinions around specific longtermist interventions seem very intuition-based and kind of arbitrary. Especially around AI, there seem to be a bunch of key considerations that many people disagree about - so it's tricky to have a strong set of agreements to do evaluation around.
6. Some people seem to think that basically nothing in AI Safety is very promising yet, so we're just trying a bunch of stuff and hoping that eventually strong research programs are evident.

I'd like to see more work here and really hope that things mature.

My somewhat "cynical" answer is that an important function of charity evaluation organisations is to challenge the status quo. If everyone is funding animal shelters and you think that's ineffective, you might as well create an organisation to redirect funding to more effective interventions. But longtermism as a field is already "owned" by EA, so EAs are unlikely to feel a need to shake up the establishment there.

I am surprised no one has directly made the obvious point of there being no concrete feedback loops in longtermist work, which means that it would be very messy to try and compare. While some people have tried to get at the cost effectiveness of X-risk reduction, it is essentially impossible to be objective in evaluating how much a given charity has actually reduced X-risk.  Perhaps there is something about creating clear proxies which allows for better comparison, but I am guessing that there would still be major disagreements over what could be best that are unresolvable.

Any evaluation would have to be somewhat subjective and would smuggle in a lot of assumptions about their worldview. I think you really can't do better than trying to evaluate people's track records and the quality of their higher level reasoning, which is essentially the meaning of grantmakers' statements like "just trust us".

Perhaps there could be something like a site which aggregates the opinions of relevant experts on something like the above and explains their reasoning publically, but I doubt this is what you mean and I am not sure this is a project worth doing.

I have made early steps towards this. So far funder interest has been a blocker, although perhaps that doesn’t say much about the value of the idea in general.

I suggest that charity evaluators generally work best, inter alia, when: (1) the charities to be evaluated are somewhat established such as to allow evaluation of a track record; (2) the charities are offering a "stable" enough intervention that a review should largely remain valid for at least a few years; (3) a field isn't moving/evolving so quickly that prior reviews will age out quickly; and (4) there's enough room for more funding in the top-evaluated orgs that would counterfactually go unfilled to make the process worthwhile. All of those conditions seem much less present in longtermism.

My sense is that at least the top 20% or so longtermist org are very likely to be funded anyway. In contrast, global health or animal orgs can almost always use more money at only a slight reduction in marginal cost-effectiveness. Finally, it's probably relevant that those orgs are competing for resources from non-EA donors with mainstream NGOs in a way that longtermist EA orgs generally aren't.

We've been doing a fair amount of work in this direction at Founders Pledge in "epistemically mildly" longtermist areas, such as climate or nuclear risk --areas that are clearly much more uncertain than RCT-global-health but probably a fair amount less cluelessless-riddled than the most intractable longtermist interventions where there is little agreement on the sign of interventions.

We are describing some of the ideas here (and, initially, in our Changing Landscape report), my colleague Christian Ruhl has also just published a report using some of those ideas to allow evaluating nuclear risk interventions, and I expect we do a fair bunch more of this work.

It is my impression that there is a bunch of low-hanging fruit here, that methodology to prioritize in high-uncertainty contexts could be a lot more developed than it is.

A lot of this is early-stage and pre-quantification (and the quantified stuff is not ready for publication yet), but it is something we are thinking about a lot (though, as per Jeff, we are quite small and, as per Nuno, it might take seven years for something like this to become good!).

(Sorry for a post mostly containing links to FP work, but they seem relevant to the discussion here).


 

GiveWell and ACE (aspirationally):

• provide highly quantified results
• have relatively small confidence intervals
• have high transparency and generally justify their beliefs.

And even then, they're not doing great on these on an absolute scale. Estimates for a given x-risk intervention are going to be many orders of magnitude harder to quantify than bednets, and interventions that are longtermist but not x-risk-related harder still. 

I have no inside information, but I think a major reason OpenPhil doesn't want small donations is that they don't want to have to justify their investments, when legible justification is basically impossible. 

Grantmakers could probably provide more information about their grants than they currently do; there are several posts on this forum explaining why they don't. 

I'd be pretty excited to see a new platform for retail donors giving to x-risk charities. For this, you'd want to have some x-risk opportunities that are highly scaleable (can do ≥ $10m p.a., will execute the project over years reliably without intervention or outside pressure), measurable (you can write out a legible, robust, well-quantifed theory of change from marginal dollars to x-risk), have a pretty smooth returns curve (so people can have decent confidence that their donations have the returns that they expect, whether they are a retail donors or a large donor). And then you could build out cost effectiveness models given different assumptions about values (e.g. time preference, population ethics) and extinction risk models that people might have, and offer retail donors a few different ways of thinking about and modeling the impacts of their donations (e.g. lives saved, micro- or picodooms).

I'd guess there are some bio interventions that fit these criteria. For AI safety there could be a crowd-funded compute cluster for safety research. This could be pretty boring and difficult to model robustly unless there was good reporting on the wins that came out of research using the cluster and further iteration on the model based on the track record.

Founders Pledge evaluates charities in a range of fields including global catastrophic risk reduction. For example, they recommend NTI’s biosecurity work, and this is why GWWC marks NTI's bio program as a top charity. Founders Pledge is not as mature as GiveWell, they don't have the same research depth, and they're covering a very broad range of fields with a limited staff, but this is some work in that direction.

First instinctive intuitive reaction - because it is not so easy, not so obvious how to measure, evaluate, quantify.

I actually posted a few days ago - https://forum.effectivealtruism.org/posts/xNyd8SuTzsScXc7KB/measuring-impact-ea-bias-towards-numbers - I made a hypothesis (based on own observations and face-to-face conversations) that there is a bias towards easily quantifiable projects.

Because the question is impossible to answer. 

First, by definition, we have no actual evidence about outcomes in the long-term future--it is not as if we can run RCTs where we run Earth 1 for the next 1,000 years with one intervention and Earth 2 with a different intervention. Second, even where experts stand behind short-term treatments and swear that they can observe the outcomes happening right in front of them (everything from psychology to education to medicine), there are many cases where the experts are wrong -- even many cases where we do harm while thinking we do good (see Prasad and Cifu's book Medical Reversals). 

Given the lack of evidentiary feedback as well as any solid basis for considering people to be "experts" in the first place, there is a high likelihood that anything we think benefits the long-term future might do nothing or actually make things worse. 

The main way to justify long-termist work (especially on AGI) is to claim that there's a risk of everyone dying (leading to astronomically huge costs), and then claim that there's a non-zero positive probability of affecting that outcome. There will never be any evidentiary confirmation of either claim, but you can justify any grant to anyone for anything by adjusting the estimated probabilities as needed.