Why "cause area" as the unit of analysis?

I like this answer.

I think it's basically a nonsense to try to compare "cause areas" without reference to specific things you can do, aka solutions. Hence, when we say we're comparing "cause areas" what we are really doing is assessing the best solution in each cause area "bucket" and evaluating their cost-effectiveness. The most important cause = the one with the very most cost-effective intervention.

Maybe a minor point, but I don't think this is quite right, because: 

• I don't think we know what the best solution in each "bucket" is
• I don't think we have to in order to make educated guesses about which cause area will have the best solution, or will have the best "identifiable positive outliers" (or mean, or median, or upper quartile, or something like that)
• I don't think we only care about the best solution; I think we also care about other identifiable positive outliers. Reasons for that include the facts that:
  • we may be able to allocate enough resources to an area that the best would no longer be the best on the margin
  • some people may be sufficiently better fits for something else that that's the best thing for them to do
  • (And there are probably cases in which we have to or should "invest" in a cause area in a general way, not just invest in one specific intervention. So it's useful to know which cause area will be able to best use a large chunk of a certain type of resources, not just which cause area contains the one intervention that is most cost-effective given generic resources on the current margin.)

For example, let's suppose for the sake of discussion that technical AI safety research is the best solution within the x-risk cause area, that deworming is the best solution in the global health & development[1] cause area, and that technical AI safety is better than deworming.[2] In that case, in comparing the cause areas (to inform decisions like what skills EAs should skill up in, what networks we should build, what careers people should pursue, and where money should go), it would still be useful to know what the other frontrunner solutions are, and how they compare across cause areas.

(Maybe you go into all that and more in your thesis, and just simplified a bit in your comment.)

[1] The fact that this is a reply to you made it salient to me that the term "global health & development" doesn't clearly highlight the "wellbeing" angle. Would you call Happier Lives Institute's cause area "global wellbeing"?

[2]  Personally, I believe the third claim, and am more agnostic about the other two, but this is just an example.

[I think the following comment sounds like I'm disagreeing with you, but I'm not sure whether/how much we really have different views, as opposed to just framing and emphasising things differently.]

So it feels like "cause prioritization" is just a first step, and by the end it might not even matter what cause areas are. It seems like what actually matters is producing a list of individual tasks ranked by how effective they are.

I agree that cause prioritization is just a first step. But it seems to me like a really useful first step. 

It seems to me like it'd be very difficult, inefficient, and/or unsuccessful to try to produce a ranked list of individual tasks without first narrowing our search down by something like "cause area" seems like it'd be wildly impractical. And the concept of "cause area" also seems useful to organise our work and help people find other people who might have related knowledge, values, goals, etc.

To illustrate: I think it's a good idea for most EAs to: 

• Early on, spend some significant amount of time (let's say 10 hours-1,000 hours) thinking about considerations relevant to which broad cause area to prioritise
  • E.g., the neglectedness of efforts to improve lives in developing vs developed countries countries, the astronomical waste argument, arguments about the sentience or lack thereof of nonhuman animals
• Then gradually move to focusing more on considerations relevant to prioritising and "actually acting" within a broad cause area, as well as focusing more on "actually acting"

And I think it'd be a much less good idea for most EAs to: 

• Start out brainstorming a list of tasks that might be impactful without having been exposed to any considerations about how the scale, tractability, and neglectedness of improving wellbeing among future beings compares to that of improving wellbeing among nonhumans etc.
  • What would guide this brainstorming?
  • I expect by default this would involve mostly thinking of the sort of tasks or problems that are commonly discussed in general society
• Then try to evaluate and/or implement those those tasks
  • I'm again not really sure how one would evaluate those things
  • I guess one could at this point think about things like how many beings the future might contain and whether nonhumans are sentient, and then, based on what one learns, adjust the promisingness of each task separately
    • But it would in many cases seem more natural to adjust the value of all/most future-focused interventions together, and of all/most animal-focused interventions together, etc.

All that said, as noted above, I don't think cause areas" should be the only unit or angle of analysis; it would also be useful to think about things like intervention areas, as well as what fields one has or wants to develop expertise in and what specific tasks that expertise is relevant to. 

As explained (EA Forum link; HT Edo Arad) by Owen Cotton-Barratt back in 2014, there are at least two meanings of "cause area". My impression is that since then, effective altruists have not really distinguished between these different meanings, which suggests to me that some combination of the following things are happening: (1) the distinction isn't too important in practice; (2) people are using "cause area" as a shorthand for something like "the established cause areas in effective altruism, plus some extra hard-to-specify stuff"; (3) people are confused about what a "cause area" even is, but lack the metacognitive abilities to notice this.

As noted above, personally, I usually find it most useful to think about cause areas in terms of a few broad cause areas which describe what class of beneficiaries one is aiming to help. 

I think it'd be useful to also "revive" Owen's suggested term/concept of "An intervention area, i.e. a cluster of interventions which are related and share some characteristics", as clearly distinguished from a cause area. 

E.g., I think it'd be useful to be able to say something like "Political advocacy is an intervention area that could be useful for a range of cause areas, such as animal welfare and longtermism. It might be valuable for some EAs to specialise in political advocacy in a relatively cause-neutral way, lending their expertise to various different EA-aligned efforts." (I've said similar things before, but it will probably be easier now that I have the term "intervention area" in mind.)

Two links with relevant prior discussion:

• This post's comments section
• This post's appendix

In practice, Open Philanthropy Project (which is apparently doing cause prioritization) has fixed a list of cause areas, and is prioritizing among much more specific opportunities within those cause areas. (I'm actually less sure about this as of 2021, since Open Phil seems to have made at least one recent hire specifically for cause prioritization.)

Open Phil definitely does have a list of cause areas, and definitely does spend a lot of their effort prioritising among much more specific opportunities within those cause areas.

But I think they also spend substantial effort deciding how much resources to allocate to each of those broad cause areas (and not just with the 2021 hire(s)). Specifically, I think their worldview investigations are, to a substantial extent, intended to help with between-cause prioritisation. (Though it seems like they'd each also help with within-cause decision-making, e.g. how much to prioritise AI risk relative to other longtermist focuses and precisely how best to reduce AI risk.)

I agree with your first two sentences. I feel unsure precisely what you mean by the sentence after that.

E.g., are you saying that no research organisations are spending resources trying to help people prioritise between different broad cause areas (e.g., longtermism vs animal welfare vs global health & development)? Or just that there's no research org solely/primarily focused on that?

My impression is that: 

• There were multiple orgs that were primarily focused on between-cause prioritisation research in the past
• But most/all have now decided on one or more cause areas as their current main focus(es) for now, and so now spend more of their effort on within-cause-area work
• But many still do substantial amounts of work that's focused on or very relevant to between-cause prioritisation, and may do more of that again later. E.g.:
  • Open Phil do worldview investigations
  • 80,000 Hours continue to put some hours (e.g.) into non-longtermist issues even if primarily longtermist issues are definitely their main focus
  • GPI are currently focused mostly on global priorities research that's relevant to longtermism. But much of that is directly about how much to prioritise longtermism in the first place (partly to make a better case for longtermism, but I think also partly just because they're genuinely unsure on that). And I imagine much of their work is also relevant to prioritising between other cause areas, and that they may diversify their focuses more in future.
    • Though I don't actually know a huge amount about GPI's work
• And there is also a bunch of non-research effort aimed at helping individuals think about which broad causes they want to/should focus on
  • E.g., the EA Virtual Programs partly do this

I think this definition of "cause area" is roughly how the EA community uses the term in practice, and explains a lot of why/how it's useful. It helps facilitate good discussion by pointing towards the best people to talk to, since others in my cause area will have common knowledge and interests with myself and each other. On this view, "cause area" is just EA-speak for a subcommunity.

That makes it a bit hard to justify the common EA practice of "cause prioritization" though, since causes aren't really particularly homogeneous with regard to their impact. I think doing "intervention prioritization" would be a lot more useful, even though there's way more interventions than causes.

That one is linked from Owen's post.

Nice find!