November 18, 2016
In this 2016 talk, Oxford University's Owen Cotton-Barratt discusses how effective altruists can improve the world, using the metaphor of someone looking for gold. He discusses a series of key effective altruist concepts, such as heavy-tailed distributions, diminishing marginal returns, and comparative advantage.
The below transcript is edited for readability.
The central metaphor that is going to be running through my talk is ‘effective altruism as mining for gold’. And I’m going to keep on coming back to this metaphor to illustrate different points. Gold, here, is standing in for whatever it is that we truly value. Some things that we might value include making more people happy and well-educated. Or trying to avert a lot of suffering. Or trying to increase the probability that humanity makes it out to the stars. When you see gold, take a moment to think about what you value. Many people won’t just value one particular thing. However, do think about what you care about and put that in place of the gold. This way, there are lots of observations we can make.
This (figure 2) is a photo of Viktor Zhdanov, and I learned about him by reading Will MacAskill’s book ‘Doing Good Better’. He was a Ukrainian biologist, who was instrumentally extremely important in getting an eradication program for smallpox to occur. As a result, he probably was counterfactually responsible for saving tens of millions of lives.
Obviously, we don’t all achieve this. But by looking at examples like this, we can notice that some people manage to get a lot more gold, manage to accomplish a lot more of whatever we altruistically value, than others. And that is reason enough to make us ask questions like: what is it that gives some people better opportunities than others? How can we go and find opportunities like that?
Elsewhere in this conference, there are going to be treasure maps and discussions of where the gold is. I’m not going to do that in this talk. I’m instead going to be focusing on the tools and techniques that we can use for locating gold, rather than trying to give my view of where it is directly.
I want to say a little bit about why I’m even using a metaphor -because we care about these things. We care about a lot of these big, complicated, valuable things. Why would I try and reduce that down to gold? Well, it is because of where I want the focus of this talk to be. I want the focus to be on techniques, tools and approaches that we can use. And if you have complex values, these would just keep on pulling your attention. But a lot of the things that we might do to try to identify where valuable things are, and how to go and achieve them, are constant, regardless of what the valuable thing is. So, by replacing them with a super simple stand-in for value, I think it helps to put the focus on this abstract layer that we are putting on top of that.
The first thing I’m going to talk about is the fact that gold, like literal gold, is pretty unevenly spread around the world. There are loads of places with almost no gold at all, and then there are a few places where there’s a big seam of gold running into the ground. This has some implications. One is that we would really like to find those seams.
Another is about sampling. For some quantities, say if I want to know roughly how tall people are, sampling five people, measuring their height and saying, “Well, the average is probably like that” is not a bad methodology. However, if I want to know on average how much gold there is in the world, sampling five random places, and measuring that, is not a great methodology, because it’s quite likely that I’ll find five places where there’s no gold, and I’ll significantly underestimate. Or possibly, one of them will have a load of gold, and now I’ll have a massively inflated sense of how much gold there is in the world.
This is a statistical property that loosely gets called having a heavy tail on the distribution. This here on the left is a distribution without a heavy-tail (Figure 6). There is a range of different amounts of gold in different places, but none of them has massively more or massively less than typical.
On the right, in contrast, is a heavy-tail distribution. It looks similar-ish to the one on the left-hand side, but there’s this long tail, getting up to vast amounts of gold, where the probabilities aren’t dying off very fast. This has implications.
Here is another way of looking at these distributions (Figure 7). In this case, I’ve arranged, going from left to right, the places in order of increasing amounts of how much gold they have. The percentiles are on the horizontal axis and the amount of gold on the vertical axis. In this case, the area beneath the graph is coloured in. That is because that quantity - that area - is meaningful. It corresponds to the total amount of where that gold is. So, on the left of the distribution that is not heavy-tailed, I can see that the gold is fairly evenly spread across a lot of different places. If we want to just get most of the gold, what is important is getting to as many different places as possible.
Solar power is like this. Sure, some places get more sunlight than other places, but the amount of solar power you generate depends more on how many total solar panels you have, than on exactly where you place them.
Over on the right, though, we have a distribution where you can see a lot of the area that spikes on the right-hand side. This just means that a lot of the gold, and if this is an actual stand-in for something that we value, a lot of what is valuable comes in this extreme of the distribution of things, which are just unusually good.
Literal gold, I think, is distributed like this. Disclaimer, I’m not a geologist, I don’t know anything about gold, but I understand that this is right. We might ask, is this also true of opportunities to do good in the world? Here is some support for this.
When we look into the world, and it’s pretty complex, we do see distributions with this heavy-tail property coming up in a lot of different places (figure 8). There are some theoretical reasons to expect certain types of distributions to arise. And this is also the case empirically if we go and look at something like income distributions around the world. Again this is a percentile version, and you can see the spike in the graph.
So this is what we find if we just go and look at the world. Obviously, there are lots of things as well that don’t have this property. But the more we look at things that are complex systems with lots of interactions, the degree to which we see this property increases. That is a big feature of lots of ways that we try and interact to improve the world.
I can also just try and look explicitly at opportunities to do good. And I can see a couple of reasons why I personally am convinced that we get some of this property. So, one reason is just convincing arguments. If I care about stopping people starving, and I do care about stopping people starving, I could ask: should I be interested in direct famine relief and trying to get food to people who are starving today? I can compare this to something more speculative. I personally have been convinced by the arguments in this book, that it would be more effective to focus on researching solutions for feeding vast numbers of people if agriculture collapses. It’s pretty extreme. It’s not something we usually think about, but I think that the argument basically checks out. I’m just limiting myself here to trying to feed people, and one of the mechanisms looks much more effective than the other.
I can also look at data (Figure 9). This is data from DCP2, which has tried to estimate the cost-effectiveness of lots of different developing world health interventions. The x-axis is on a log scale, so these have been put into buckets, and each column is on average ten times more effective to than the one on its left. Here the rightmost column is about 10,000 times more effective than the leftmost column. And this was just within one area where we have managed to get good enough data that we can go and estimate these things. There is just a very wide range of cost effectivenesses.
The implications of this are that if we want to go and get gold, we really should focus on finding seams. In some cases, it might give us a surprising conclusion, say you discover that something is at the 90th percentile, that might make us less excited about it. Because before we knew anything, it might have been anywhere on the distribution. And if most of the possible value of it comes from it being up at the 99th percentile, then discovering it’s only at the 90th percentile could actually be a bad thing. I mean, it’s a good thing to discover, but it makes us think less well of it. Now, that’s if you’ve got a fairly extreme distribution, but it’s interesting to see how you can get these kinds of counterintuitive properties.
Another implication is that a kind of naïve empiricism, “we’ll just do a load of stuff and see what comes out best”, isn’t going to be enough for us in judging this, because of this sampling issue. We can’t go and sample enough times and measure the outcomes well enough to judge how effective it is really going to be.
If we want to get as much gold as possible, we want to go to a place where there is lots of gold. We want to have the right tools for getting the gold out, and we want to have a great team that is going to be using those tools. I think that we can port this analogy over to opportunities to doing good as well. We can roughly measure the effectiveness of the area or type of thing that we’re doing, and the effectiveness of the intervention that we’re implementing to create value in that area, relative to other interventions in the area. We can measure the effectiveness of the team or the organisation which is running the implementation, relative to how well other teams might implement such an intervention.
And if you have these things then the total value that you are going to be getting is equal to the product of these. I’ve represented it here by volume, and we want to be maximising the volume (Figure 11). That means we’re going to want to be trying to do reasonably well on each of the different dimensions. At least, not terribly on any of the dimensions. Some implications here might be that if we have an area and an intervention that we’re excited about, but we can only find a kind of mediocre team working on it, it may be better not just to support them, but to try and get somebody else working on it. Or to do something to really improve that team. Similarly, we might not want to support even a great team, if they’re working in an area that doesn’t seem important.
In the next section, I am going to talk about the tools and techniques for identifying where in the world gold is. A nice property of literal gold is that when you dig it up, you’re pretty sure that you can recognise “yes I have gold”. We often have to deal with cases where we don’t have this. We don’t have the gold, so we have to carefully try to infer its existence, by using different tools. This fact is like the dark matter of value.
This fact increases the importance of actually applying those tool diligently. Actually, the picture I showed you (Figure 12) was iron pyrite, not gold. So just because somebody says, “Hey, this is gold,” doesn’t mean we should always take people’s word for it. It does provide some evidence, but we have motivation for wanting to have great tools for identifying particularly valuable opportunities. And being able to differentiate and say, “Okay, actually this thing, although it has some aspects of value, may not be what we want to pursue.”
This fact increases the importance of actually applying those tool diligently. Iron pyrite also looks a lot like gold, so just because somebody says, “Hey, this is gold,” doesn’t mean we should always take people’s word for it. It does provide some evidence, but we have motivation for wanting to have great tools for identifying particularly valuable opportunities. And being able to differentiate and say, “Okay, actually this thing, although it has some aspects of value, may not be what we want to pursue.”
If you first go to an area where nobody has been before, then the seams of gold that are running through the ground have often been eroded a little bit, and you can have little nuggets of gold just lying around on the ground, and it’s extremely easy to get gold. So you have some people go in, they do this for a bit, and they run out of all the gold on the ground.
And now, if they want to get more gold, maybe more people come along, they bring some shovels, and it is a bit more work, but you can still get gold out (figure 15).
And then you dig deep enough, and you can’t just get in with shovels anymore, so you need bigger teams and heavier machinery to get gold out (figure 16). You can still get gold, but it’s more work for each little bit, for each nugget that you’re getting out. This is the general phenomenon of ‘diminishing returns’ on work that you’re putting in. This concept comes up in a lot of different places, and so it is worth having an understanding of it.
By the way, this, like several of the things I’m going to be talking about, is a concept, which is native to economics. And in some cases, I’m merely just pulling this from economics, and in some cases, there’s a little bit more modification on the concept.
For instance, I think that we get this in global health. I understand that 15 or 20 years ago, mass vaccinations were extremely cost-effective and probably the best thing to be doing. Then the Gates Foundation has come in and funded a lot of the mass vaccination interventions. Now, the most cost-effective intervention is less cost-effective than mass vaccinations. That is great because we have taken those low hanging fruit. Or similarly, if in AI safety, writing the first book on superintelligence is a pretty big deal. Writing the 101st book on superintelligence is just not going to matter as much.
So, a minute ago, I talked about how we could factor the effectiveness of organisations into the area which it was working on, the intervention it is pursuing, and the team working on it. Now, I’m going to focus on that first one, trying to assess the area. And I’m going to give a further factorisation, splitting this into three different things.
The first of these dimensions is scale. All else being equal, we would prefer to go somewhere where there is a lot of gold, rather than a little bit of gold. And probably per unit efforts, we are going to get more gold, if we do that.
Second: tractability. We’d like to go somewhere where we make more progress per unit work. Somewhere, where it’s nice and easy to dig the ground, rather than trying to get your gold out of a swamp.
And third is uncrowdedness. This has sometimes been called neglectedness. I think that term is a bit confusing. It’s a bit ambiguous because sometimes people use ‘neglectedness’ to mean that this is an area which we should allocate more resources to. What I mean here is that there aren’t many people looking at it. All else being equal, we would rather go to an area where people haven’t already picked up the nuggets of gold on the ground, than one where they have. And now the only gold remaining is quite hard to extract.
Ideally, of course, we’d like to be in the world where there is loads of gold, that’s easier to get out, and nobody has taken any of it. But, we are rarely going to be in that exactly ideal circumstance. So one question is: how can we trade these off against each other? I’m going to present one attempted way to try and make that precise. I’ve allowed myself one equation in this talk. This is it (figure 20).
If you’re not used to thinking in terms of derivatives, just ignore the ‘ds’ here [Figure 20]. But on the left is the value of a little bit of extra work, so this is what we care about if we’re trying to assess which of these different areas we should do more work on.
On the right is a factorization. This is mathematically trivial, I’ve just taken this one expression, and I’ve added a load more garbage. And on the face of it, it looks like I’ve made things a lot worse. I can only justify this, if it turns out that these terms I’ve added in, which cancel each other out, actually mean that the right-hand side here is easier to interpret or easier to measure. So I’m going to present a little bit of a case for why I think it is.
The first term is measuring the amount of value you get for, say, solving an extra one percent of a solution. And that roughly tracks how much of a big deal the whole problem that you’re looking at is, the whole area. I think that is a pretty precise version of the notion of scale.
The second one is a little bit more complicated. It is an elasticity here, which is a technical term. It’s a pretty useful and general term (go look it up on Wikipedia, if you’re interested). Here, it is measuring, for a proportional increase in the amount of work that’s being done, what proportion of a solution that gives you.
The final term just cancels to one over the total amount of work being done. So that is very naturally a measure of uncrowdedness.
People have talked about this kind of scale, tractability, uncrowdedness framework for a few years without having a precise version. That means that people have given different characterizations of the different terms, and I think there have been a few different versions of tractability, not all of them lining up with this exactly. But I think that this idea of it - measuring how much more work gets you towards a solution - is fairly well captured here.
I think that all of these dimensions matter. And again, that means we probably don’t want to work on something, which does absolutely terribly on any of the dimensions. I’m not going to spend an hour helping a bee, even if nobody else is helping it and it would be pretty easy to help, because just the scale of it is pretty small. I don’t think we should work on perpetual motion machines, even though basically nobody is working on it and it would be really fantastic if we succeeded. Because it seems like it’s not tractable.
And this (...) might give us a warning against actually working on climate change. Because at a global scale, that gets a lot of attention, as a problem.
I’m going to add some more caveats to that one. One is that this is going to be true while we think that there are other problems, which are just significantly more under-resourced. And another is that you might think that you have an exception if you have a much better way of making progress on the problem of climate change than typical work that is done on it.
Even so, I think maybe we should think it’s a bit surprising that I’m making a statement like “climate change is not a high priority area.” This just sounds controversial and we should be sceptical of this. But, I think that the term high priority is a little bit overloaded. And so I want to distinguish that a little bit.
If we have these two places where there’s gold in the ground, and we say: “Where should we send people if we want to get gold?” The answer is going to depend. Maybe we send the first person to this place on the right, where there’s only a little bit of gold, but it’s really easy to get out. Then we send the next ten people to the place on the left, just because there’s more total gold there. The first person will already have gotten most of the gold on the right. And we want more people total working on this place on the left. Which of these is the higher priority? Well, that just depends on which question you’re asking.
These numbers are just made up off the top of my head, but we might have some distribution like this on the left. Here, we ask the question “How much should the world spend on this area, total?” and we get one distribution, where maybe climate change looks very big.
And if we instead ask, how valuable is marginal spending? The graph might look quite different because here it is significantly about how much is already being spent. You’ll see some dotted black lines on the diagram on the left (Figure 23) - they might represent how much is already being spent. Then, the graph on the right is a function of all sorts of things, like how much should be spent in total, how much is already being spent and of course, what the marginal returns are - what the curve looks like there.
But I think that both of these are important notions, and which one we use should depend on what we are talking about. If we are having a conversation about what we as individuals or as small groups should do, I think it’s appropriate to use this notion of marginal priority, of how much do extra resources help. If we’re talking about what we collectively as a society or the world should do, I think it’s often correct to talk about this kind of notion of absolute priority and how much resources ought to be invested in it, total.
Okay, for most of the things here, I’ve been extremely agnostic about what our view of value is. Just for this point, I’m going to start making more assumptions. I think quite a few people have the view that what we want to do is try and make as much value over the long term, as we can. Some people don’t have that view, some people haven’t thought about it. If you don’t have that view, you can just treat this as a hypothetical: “Now I can understand what people with that view would think.” If you haven’t thought about it, go away and think about it, some time. It’s a pretty interesting question, and I think it’s an important question, and is worth spending some time on.
But, if we do care about creating as much value in the long term as possible, in our gold metaphor, that might mean wanting to get as much gold out of the ground eventually, as possible, rather than just trying to get as much gold out of that ground this year.
And maybe we have some technologies which are destructive. So we can use dynamite and dynamite gets us loads of gold now, but it also blows up some gold, and now we never get that gold later. That could be pretty good if you are focusing just on trying to get gold in the short term. But it could be bad from this eventual gold perspective.
If we have different technologies that we can develop, maybe we can develop some that are also efficient but less destructive. And there are going to be some people in the world who do care about creating as much gold as possible in the short term. They are going to use whichever technology is the most efficient for that. And so one of the major drivers of how much gold is eventually extracted is the order in which the technologies are developed, and the sequencing. If we discover the dynamite first, people are going to go and have fun with their dynamite and they’re going to destroy a lot of the gold. If we discover the drill first, then by the time dynamite comes along, people will go “Well, why would we use that? We have this fantastic drill.”
Philosophers like Nick Bostrom have used this to argue for trying to develop societal wisdom and good institutions for decision making, before developing technologies or progress which might threaten the long-run trajectory of civilization. And also for trying to focus on differentially aiming to develop technologies which enhance the safety of new developments, rather than or before anything that’s driving risk.
Now, I’m going to talk about how this is a collaborative endeavour. We’re not just all, each of us individually, saying: “I need to work out where the most gold is. And that’s most neglected, most tractable. I personally am just going to go and do that.” Because there is a whole lot of people who are thinking like this, and there are more every year. I am really excited about this. I’m excited to have so many people here and also this idea that maybe in two years time, we’ll have a lot more again.
But we need to work out how to cooperate. Largely, we have the same view or pretty similar views on what to value. Maybe some people think that silver matters, too - it’s not just gold - but we all agree that gold matters. We’re basically cooperating, here. We want to be able to coordinate and make sure that we’re getting people working on the things which make the most sense for them.
There is this idea of comparative advantage. On this graph (Figure 25), I have Harry, Hermione and Ron, and they have three tasks that they need to do to get some gold. They need to do some research, they need to mix some potions, and they need to do some wand work. Hermione is the best at everything, but she doesn’t have a time turner, so she can’t do everything. So we need to have some way of distributing the work. This is the idea of comparative advantage. Hermione has an absolute advantage on all of these tasks, but it would be a waste for her to go and work on the potions because Harry is not so bad at potions. And really, nobody else is at all good at doing the research in the library. So we should probably put her on this.
And this is a tool that we can use to help guide our thinking about what we should do as individuals. If I think that some technical domain and technical work is the most valuable thing to be doing, but I would be pretty mediocre at that, and I’m a great communicator? Then maybe I should go into trying to help technical researchers in that domain communicate their work to get more people engaged with it and bring in more fantastic people.
Now we have applied this at an individual level. We can also apply this at the group level. We can notice that different organizations or groups may be better placed to take different opportunities.
This is a bit more speculative, but I think we can also apply this at the time level. We can ask ourselves, “What are we, today, the people of 2016, particularly well suited to do, versus people in the past and people in the future?” We can’t change what people in the past did. But we can make a comparison of what our comparative advantage is relative to people in the future. And if there is a challenge, if there were going to be some different possible challenges in the future that we need to meet, it makes sense that we should be working on the early ones. Because if challenges are coming in 2020, the people in 2025 just do not have a chance to work on that.
Another thing which might come here is that we have a position, perhaps, to influence how many future people there will be who are interested in and working on these challenges. We have more influence over that than people in that future scenario do, so should we think about whether that makes sense as a thing for us to focus on?
Another particularly important question is how to work stuff out. The world is big and complicated and messy. And we can’t expect all of us, individually, to work out perfect models of it. In fact, it is too complicated for us to expect anybody to do this. So, maybe we’re all walking around with the little ideas which, in my metaphor here, are puzzle pieces for a map to where the gold is. We want institutions for assembling these into a map. It’s a bit complicated, because some people have puzzle pieces which are from the wrong puzzle, and they don’t track where the gold is. Ideally, we would like our institutions to filter these out and only assemble the correct pieces to guide us where we want to go.
As a society, we have had to deal with this problem in a number of different domains, and we have developed different institutions for doing this. There is the peer review process in science. Wikipedia does quite a lot of work aggregating knowledge. Amazon reviews aggregate knowledge that individuals have about which products are good. Democracy lets us aggregate preferences over many different people to try and choose what’s going to be good.
Of course, none of these institutions is perfect. And this is a challenge. This is like one of those wrong puzzle pieces, which made it into the dialogue. And this comes up in the other cases as well. The replication crisis in parts of psychology has been making headlines recently. Wikipedia, we all know, sometimes gets vandalized, and you just read something which is nonsense. Amazon reviews have problems with people giving fake reviews, to make their product look good or other people’s products look bad.
So, maybe it is the case that we can adapt one of these existing institutions for our purpose, which is trying to aggregate knowledge about what are the ways to go and do the most good. But maybe we want something a bit different, and maybe somebody in this room is going to do some work on coming up with valuable institutions for this. I actually think this is a really important problem. And it’s one that is going to become more important for us to deal with as a community, as the community grows.
That was all about what are our global institutions for pulling this information together and aggregating it. Another thing, which can help us to move towards getting a better picture, is trying to have good local norms. So, we tell people the ideas that we have, and then other people maybe start listening. And sometimes it might just be that they listen based on the charisma of the person who is talking, more than based on the truthiness of the puzzle piece. But we would like to have ways of promoting the spread of good ideas, inhibiting the spread of bad ideas, and also encouraging original contributions. One way of trying to promote the spread of good ideas and inhibit bad ideas is just to rely on authority. We’ll say, “Well, we’ve worked out this stuff. We’re totally confident about this. And now we just won’t accept anything else.” But that isn’t going to let us get new stuff.
I think something to do here is to pay attention to why you believe something. Do you believe it because somebody else told you? Do you believe it because you have really thought this through carefully and worked it out for yourself? There is a blur between those. Often somebody tells you, and they give you some reasons. And you are thinking: “Oh, those reasons kind of check out,” but you haven’t deeply examined the argument yourself.
I think it’s useful, to be honest with yourself about that. And then also to communicate it to other people. To let them know why it is. Is it the case that you believe this because Joe Bloggs has told you? And actually, Joe is a pretty careful guy, and he is pretty diligent about checking out his stuff, so you think it probably makes sense. You can just communicate that. Or is it that you cut out this puzzle piece yourself?
Now, cutting it out yourself doesn’t necessarily mean we should have higher credence in it. I have definitely worked things out, and I have thought I have proved things before, and there was a mistake in my proof. So you can separately keep track of the level of credence you have in a thing, and why you believe it.
Also, our individual and collective reasons for believing things can differ. Here is this statement, that it costs about $3,500 to save a life from malaria. I think this is broadly believed across the effective altruism community. I think that collectively, the reason we believe this is that there have been a number of randomized control trials. And then some pretty smart, reasonable analysts at GiveWell have looked carefully at this, and they have dived into all the counterfactuals, and they have produced their analysis, and come to the conclusion: “On net, it looks like it’s about $3,500.”
But that isn’t why I believe it. I believe it because people have told me that the GiveWell people have done this analysis and they say it’s $3,500. And they say, “Oh, yeah. I read it on the website.” That was why I believed it until I started prepping for this talk when I went and read it on the website. Because I think that this is a bit more work for me, but it’s doing a bit of value for the community. I’m shortening the chain of Chinese whispers, of passing this message along. And as things get passed along, it’s possible that mistakes enter or just something isn’t well grounded, and then it gets repeated. By going back and checking earlier sources in the chain, we can try to reduce that, and try to make ourselves more robustly confident in these statements.
Another thing that comes up is when you notice that you disagree with somebody.: If you’re sitting down and talking with someone and they’re saying something, and you think: “Well, that’s obviously false.” You can see perhaps that parts of their jigsaw puzzle are wrong. You could just dismiss what they have to say. But I think that that’s often not the most productive thing to do. Because even if part of what they have to say is wrong, maybe they have some other part that is going into their thinking process which would fill a gap in your perspective on it, and help you to have a better picture of what’s going on.
I often do this when I find that someone has a perspective that I think is unlikely to be correct. I’m interested in this process of how they get there and how they think about it. Partly this is just that people are fascinating and the way that people think is fascinating, so this is interesting. But I also think that it is polite and I think it is useful. I think it does help me to build a deeper picture of all the different bits of evidence that we collectively have.
In this section, I’m going to put the stuff I’ve just been talking about into action. I’ve told you about a whole load of different things through this talk. But I didn’t tell you much about exactly what my level of competence in these is, or why I believe these. So, I’m going to do that here.
I’m aware that nobody ever goes away from a talk saying, “Oh, that was so inspiring. The way she carefully hedged all her statements.” But I think it’s important. I would like people to go away from talks saying that. So I’m just going to do it.
Heavy-tailed distributions: I think it’s actually pretty robust that the kind of baseline distribution of opportunities in the world does follow something like this, a distribution with this heavy-tailed property. I think that just seeing this in many different domains and understanding some of the theory behind why it should arise makes it extremely likely. I think that there’s an open empirical question to exactly how far that tail goes out. Heavy-tailedness isn’t just a binary property; it’s a continuum. Anders Sandberg is going to be talking more about this, I think, later today.
But, there is an important caveat here. This is the only one of these I’ve allowed myself, a digression. It is that there is a mechanism which might push against that, which is people seeking out and taking the best opportunities. If people are pretty good at identifying the best opportunities, and they are uniformly seeking out and taking them, then the best things that are left might not be so much better.
And this comes up in just regular markets. Ways to make money, maybe they actually start out distributed across a wide range. This is a log scale now, and it is meant to represent one of those heavy-tailed distributions, but then people who are losing money, say, “Well, this sucks,” and they stopped doing that thing. And they see other people who are doing activities which are making lots of money. And they think: “Yeah, I’m going to go do that.” And then you get more people going into that area, and then diminishing returns mean that you actually make less money than you used to, by doing stuff in that area. So, afterwards, you end up with a much more narrow distribution of the value that is being produced by people doing these different things, than we started with.
We might get a push in that direction among opportunities to create altruistic value. I certainly don’t think that we are in a properly efficient market. I’m not sure how efficient it is, how much we are curving that tail. I hope that as this community grows, as we get more people who are actively trying to choose very valuable things, that will mean the distribution does get less heavy-tailed.
One of the mechanisms that lead to efficiency in regular markets is feedback loops, where people just notice they are getting rich or that they are losing money. Another mechanism is people doing analysis, and they do this because of the feedback loops, trying to work out that actually, we should put more resources there because then we’ll get richer. I think that doing that analysis is an important part of the project we’re collectively embarking on here.
Overall, I don’t think that we do have an efficient market for this. I do believe we have heavy-tailed distributions. I’m not sure how extreme, but that’s because it responds to actions people are taking.
Factoring cost-effectiveness: I think that this is just an extremely simple point, and there isn’t really space for it to be wrong. But there is an empirical question as to how much these different dimensions matter. It might be that you just have way more variation in one of the dimensions than others. Actually, I don’t have that much of a view of how much the different dimensions matter. We saw that the intervention effectiveness within global health varied by three or four orders of magnitude. Area effectiveness, I think, may be more than that, but I’m not sure how much more. In terms of organization effectiveness, I’m just not an expert, and I don’t want to try and claim to have much of a view on that.
Diminishing returns: I just think this is an extremely robust point. Sometimes, in some domains, there are increasing returns to scale, where you get efficiencies of scale, and that helps you. I think that more often applies to the organization scale or organization within a domain. Whereas diminishing returns often apply at the domain scale. But I do know some smart people who think that I am overstating the case for diminishing returns. So although I think, personally, that there’s a pretty robust case, I would add a note of caution there.
Scale, tractability, neglectedness: I think it is obvious that they all matter. I think it is obvious, it is just trivial, that this factorization is correct as a factorization. What is less clear is whether this breaks it up into things that are easier to measure and whether this is a helpful way of doing it. I think it probably is. We get some evidence from the fact that it loosely matches up with an informal framework that people have been using for a few years, and have seemed to find helpful.
Absolute and marginal priority: Again, at some level, is just trivial. I made this point about communication because I think not everybody has these separate notions and we can confuse each other if we blur them.
Differential progress: I think that this argument basically checks out. It appears in a few academic papers. It’s also believed by some of the smartest and most reasonable people I know, which gives me some evidence that it might be true, outside of my personal introspection. It hasn’t had that much scrutiny, and it’s a bit counterintuitive, so maybe we want to expose it to more scrutiny.
Comparative advantage is just a pretty standard idea from economics. Normally markets try to work to push people into working in the way that utilizes their comparative advantage. We don’t necessarily have that when we’re aiming for more altruistic value.
The application across time is also a bit more speculative. I’m one of the main people who has been trying to reason this way. I haven’t had anybody push back on it, but take it with a bit more salt, because it’s just less well checked out.
Aggregating knowledge: I think everyone tends to think that yes, we want intuitions for this. And I think there is also pretty broad consensus that the existing institutions are not perfect. Whether we can build better institutions, I’m less certain about.
Stating reasons for beliefs: this again is something that I think is common sense. All else equal, this is a good thing. But of course, there are costs to doing it. It slows down our communication. And it may just not sound glamorous and therefore be harder to get people on board with this. I think that at least we want to nudge people in this direction, but I don’t know exactly how far in this direction. We don’t want to be overwhelmingly demanding on this. I, to some extent, believe this because a load of smart, reasonable people I know, think that we want to go in this direction. And I weigh other people’s opinions when I don’t see a reason that I should have a notably better perspective on it than them.
Finally, why have I been sharing all of this with you? You know, people can go and mine gold without understanding all these theoretical arguments about the distribution of gold in the world. But, because it’s invisible, we need to be more careful about aiming at the right things. And so I think it’s more important for our community to have this knowledge broadly spread. And I think that we are still in the early days of the community and so it’s particularly important to try and get this knowledge in at the foundations and to work out better versions of this. We don’t want to have the kind of gold rush phenomenon where people charge off after a thing, and it turns out there wasn’t actually that much value there.
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- 1. Introduction to Effective Altruism
- 2. Efficient Charity — Do Unto Others
- 3. Prospecting for Gold
- 4. Crucial Considerations and Wise Philanthropy
- 5. The Moral Value of Information
- 6. The Long-Term Future
- 7. A Proposed Adjustment to the Astronomical Waste Argument
- 8. Three Impacts of Machine Intelligence
- 9. Potential Risks from Advanced AI
- 10. What Does (and Doesn’t) AI Mean for Effective Altruism?
- 11. Biosecurity as an EA Cause Area
- 12. Animal Welfare
- 13. Effective Altruism in Government
- 14. Global Health and Development
- 15. How valuable is movement growth?