A Funnel for Cause Candidates

Great point.

I think my take is that evaluation and ranking often really makes sense for very specific goals. Otherwise you get the problem of evaluating an airplane using the metrics of a washing machine.

This post was rather short. I think if a funnel became more capacity, it would have to be clarified that it has a very particular goal in mind. In this case, the goal would be "identifying targets that could be entire nonprofits". 

We've discussed organizing cause areas that could make sense for smaller projects, but one problem with that is that the number of possible candidates in that case goes up considerably. It becomes a much messier problem to organize the space of possible options for any kind of useful work. If you have good ideas for this, please do post!

I agree with this. 

I think one could address that simply by tweak the quoted sentences to "It has been determined that it's most likely a good idea to start object-level work on a specific cause/intervention (e.g., starting a charity, starting a new programme in an existing org or government, doing independent research and advising key decision-makers). Now the hard work begins of actually doing that."

(I'm also not sure the implementation stage will always or typically be harder than the other three stages. I don't specifically believe the opposite; I just feel unsure, and imagine it varies.)

One minor quibble with your comment: I think "do an Econ PhD [and during this or afterwards try to estimate the philanthropic discount rate]" should probably not by itself be called "implementation". It's more object-level than doing prioritisation research to inform whether someone should do that, but by itself it doesn't yet connect to any "directly important" decisions. So I'd want to make some mention of later communicating findings to key decision-makers.

[Btw, thanks for this post, Nuño - I found it clear and useful, and liked the diagram.]

Makes sense, thanks, changed.

Basically my point is, depending on answers to questions such as the above, you may think a longtermist cause area is WAY better than a shorttermist cause area, or vice versa, and we haven't even gone near a CEA (which I'm not sure would help matters). I can't emphasise that 'WAY' enough.

I think this is true. I therefore also basically agree with your conclusions, but I think they're much less damning than I get the impression you think. Basically, I'd rephrase your second-last paragraph to:

"So it seems worth noting that this model is probably most/only useful for the project of generating and comparing cause candidates within a cause area. E.g., it could be useful for neartermist human-focused stuff, neartermist animal-focused stuff, or longtermist stuff, but probably separately for each. 

But that alone shouldn't prevent this model from being very useful. That's because there are a huge number of ideas that could be generated, deconfused, evaluated, and implemented within each broad cause area, so a model that helps us do that for each cause area could be really handy, even if it doesn't simultaneously help us decide between broad cause areas."

[Tangent]

To some significant extent, I just think choice of cause area is quite personal. Some people are longtermists, some aren't. Some people think it's good to reduce x-risk, some don't etc. 

I think I might actually agree with what you actually mean, but not with a natural interpretation of this sentence. "quite personal" sounds to me like it means "subjective, with no better or worse answers, like how much someone likes How I Met Your Mother." But I think there may be "better or worse answers", or at least more or less consistent and thought-out answers. And I think that what's going on here is not simply subjectivity.

Instead, I'd say that choices of broad cause area seem to come down to a combination of factors like:

• One's implicit and explicit moral/normative/decision-theoretic views
  • E.g., would increasing the number of lives that occur be a good thing, if those lives are happy?
  • E.g., should people just maximise expected value? Even in Pascalian situations?
• One's implicit and explicit epistemological views
  • E.g., how much to trust inside- vs outside-views, chains of theoretical arguments vs empirical data, etc.
• One's implicit and explicit empirical views, sometimes on questions where it's unusually hard to get evidence (meaning one must rely more on priors)
  • E.g., are we at the hinge of history?
• The common assumptions, norms, social environments, etc. one is exposed to

I think people can explicitly discuss and change their minds about all of these things. 

But that seems (a lot?) harder than explicitly discussing and changing one's mind about priorities within a broad cause area. And I think this is partly because these between-cause-area stuff involves more differences in moral views, priors, etc. I think this is the sort of thing you might gesture at with "To some significant extent, I just think choice of cause area is quite personal"?

To return from my tangent to the post at hand: The activities involved in the stages of this model:

• might inform relevant empirical views, but that effect might be limited by those views sometimes being  unusually dependent on priors
•  might usually not really have much to say about relevant moral/normative/decision-theoretic views and relevant epistemological views. 

And I think that that's one way to explain why this model might not have much to say about between-cause-area decisions.

A (nit-picky) point that feels somewhat related to your points: 

I like that Nuño says "To clarify, I’m not saying that all  EA charities need to be started after a quantitative cost-effectiveness analysis."

But personally, I still feel like the following phrasing implies an emphasis on empirical data and/or a quantitative cost-effectiveness analysis:

Evaluation: How does the evidence base for this kind of intervention look? What does a cost-effectiveness analysis of proposed interventions reveal?

I think often it might make sense to also or instead emphasise things like theoretical arguments, judgemental forecasts, and expert opinions. (See also Charity Entrepreneurship's research method.) I think these things are technically evidence in a Bayesian sense, but aren't what people would usually think of when you say "evidence base". 

So personally, I think I'd be inclined to rephrase the "Evaluation" step to something like "How does the evidence base and/or reasoning for this kind of intervention look? This could include looking at empirical data, making cost-effectiveness analyses, collecting forecasts or expert opinions, or further probing and fleshing out the theoretical arguments."

So suppose you have a cause candidate, and some axis like the ones you mention:

• Degree to which the area arguably runs into the cluelessness problem
• Degree to which the area affects beings who don't exist yet / Promisingness of the area under the totalist view.
• ...

But also some others, like

• Promisingness given a weight of X humans to Y animals
• Promisingness given that humans are ~infinitely more valuable than animals
• Tractability of finding good people to get a project started
• Units of resources needed
• Probability that a trusted forecasting system gives to your project still existing in 2 years.

For simplicity, I'm going to just use three axis, but the below applies to more. Right now, the topmost vectors represent my own perspective on the promisingness of a cause candidate, across three axis, but they could eventually represent some more robust measure (e.g., the aggregate of respected elders, or some other measure you like more). The vectors at the bottom are the perspectives of people who disagree with me across some axis.

For example, suppose that the red vector was "ratio of the value of a human to a standard animal", or "probability that a project in this cause area will successfully influence the long-term future".

Then person number 2 can say "well, no, humans are worth much more than animals". Or, "well, no, the probability of this project influencing the long-term future is much lower". And person number 2 can say something like "well, overall I agree with you, but I value animals a little bit more, so my red axis is somewhat higher", or "well, no, I think that the probability that this project has of influencing the long-term future is much higher".

Crucially, they wouldn't have to do this for every cause candidate. For example, if I value a given animal living a happier life the same as X humans, and someone else values that animal as 0.01X humans, or as 2X humans,  they can just apply the transformation to my values.

Similarly, if someone is generally very pessimistic about the tractability of influencing the long-term future they could transform my probabilities as to that happening. They could divide my probabilities by 10x (or, actually, subtract some amount of probability in bits). Then the tranformation might not be linear, but it would still be doable.

Then, knowing the various axis, one could combine them to find out the expected impact. For example, one could multiply three axis to get the volume of the box, or add them as vectors and consider the length of the purple vector, or some other transformation which isn't a toy example. 

So, a difference in perspectives would be transformed into a change of basis

So:

Even in that case there's a difficulty, in that anyone who disagrees with your stance on these foundational questions would then have the right to throw out all of your funneling work and just do their own. 

doesn't strike me as true. Granted, I haven't done this yet, and I might never because other avenues might strike me as more interesting, but the possibility exists. 

[Tangent]

Do you hold a totalist view of population ethics? If you don't you may want to funnel out all x-risk reduction charities

"X-risk" is typically short for "existential risk", which includes extinction risk, but also includes risks of unrecoverable collapse, unrecoverable dystopia, and some (but not all) s-risks/suffering catastrophes. (See here.) 

My understanding is that, if we condition on rejecting totalism: 

• Risk of extinction becomes way less important
  • Though it'd still matter due to its effects on the present generation
• Risk of unrecoverable collapse probably becomes way less important (though this is a bit less clear)
• Risk of unrecoverable dystopia still retains much of its importance
• Suffering risk still retains much of its importance

(See here for some discussion relevant to those points.)

So maybe by "x-risk" you actually meant "extinction risk", rather than "existential risk"? (Using "x-risk"/"existential risk" as synonymous with just "extinction risk" is unfortunately common, but goes against Bostrom and Ord's definitions.)