[Epistemic status: strongly stated, weakly held]
When faced with problems that involve ongoing learning, most strategies involve a balance between "exploration" and "exploitation". Exploration means taking opportunities that increase your knowledge about how good your opportunities are, whereas exploitation means putting resources into what you currently believe is the best opportunity. A good strategy will involve both: if you only explore, then you will never actually reap any rewards, whereas if you only exploit then you will likely spend all your resources on a poor opportunity.
When we in the EA community are thinking about how to spend our resources, we face an exploration/exploitation problem. In this post I'm going to argue that:
- The value of exploration is higher than ever
- The EA community is not doing enough exploration
- Exploration through experimentation is particularly neglected
Preface: What does exploration and exploitation look like for EA?
I'm deliberately going to leave these terms fairly vague - I'm not entirely sure that they can be made precise in this context1. However, here are some canonical exemplars of what exploration and exploitation look like in the setting of EA:
- Doing or donating to the best direct work that you know of is exploitation.
- Trying to work out what to work on or donate to is exploration.
We actually have two additional options that aren't available in traditional exploration/exploitation problems:
- Increase our exploitation capacity. This represents how effectively we can exploit good opportunities, so includes things like increasing our available funds or people.
- Increase our exploration capacity. This represents how effectively we can explore, so includes things like increasing our pool of available researchers or forming better exploration institutions.
The value of exploration is higher than ever
Exploration improves the effectiveness of exploitation, because we may discover that we can switch our resources to a better opportunity. If GiveWell discovered a new top charity that was significantly more effective than its current ones, then many EAs who are donating (exploiting) might switch their donations to that charity, increasing the amount of good they achieved with their exploitation.
"Smart money" (and, although it's less fungible, "smart capacity" like talented employees) corresponds to our exploitation capacity. The greater our exploitation capacity, the more benefit we gain from moving our resources to a better opportunity, and so the more valuable it is to explore.
We actually have a couple of quantitative models of how useful exploration is:
- Some old work of mine estimating the value of funding the Disease Control Priorities (DCP) project (part 1, part 2).2
- Peter Hurford's model of how valuable it is to create a new GiveWell-recommended charity.
Both of these models suggest that the cost-effectiveness of spending on exploration could be many times that of spending on exploitation (funding charities), and that the value of exploration is greatly increased by the amount of "smart money" that can be directed by improved information.
The improvement from more exploration may not be a simple multiplier on the effectiveness of our exploitation (as is assumed in e.g. the DCP model), because opportunities do not have an unlimited capacity to absorb resources. If anything, this makes exploration more important: if we do not explore enough then we are at risk of running out of effective ways to spend our resources, in which case we would have to fall back on worse opportunities or just save our money.3
The EA community has recently seen a vast increase in its exploitation capacity. Not only has the community expanded a great deal, but the Open Philanthropy Project (OPP) now has the potential to provide a vast amount of funding. That means that exploration (and hence improving exploration capacity) is increasingly valuable, since it has the potential to enhance a huge budget.
The EA community has benefited from an excellent initial endowment of exploration done by the academic community (Glennerster and Kremer; DCP), and later GiveWell and Giving What We Can. That means that there has been plenty of low-hanging fruit available for collection, if we could get the resources to harvest it. So we have largely been able to focus on improving exploitation (outreach).
That doesn't mean that we haven't increased our exploration capacity: today there is more exploration happening than ever, with all of the existing research organizations having increased their capacity, and new organizations like OPP also doing exploration work.
However, the total amount of effort expended in this direction by the EA community is still small relative to how much our exploitation capacity has improved. I very roughly estimate the number or researchers doing exploratory work at <100.4 These jobs also tend not to be incredibly highly-paid, so at a generous assumption of ~$50k per person, and doubling to allow for support staff, that's still less than $10m being spent on research by the movement as a whole.5
In comparison, OPP alone expects to have disbursed about $100m in grants in 2016, and eventually to grant as much as $400m a year.
I don't have a good idea for what kind of spending ratio would be ideal, but this seems low to me (more precise models welcome!). As a heuristic, I think most EAs would consider RCTs to be a cost-effective way of getting high-quality information about a possible solution. But the EA community has spent almost no money on funding RCTs!6 Hopefully this means that we are spending our money doing exploration that is even more valuable than RCTs, but that means that we have not even progressed far enough up the curve of diminishing marginal returns to exploration to reach "doing RCTs".
Exploration through experimentation is particularly neglected
From an exploitation point of view, all of these are equivalent:
- Discovering a good opportunity
- Discovering that a known opportunity is good
- Creating a new good opportunity
In all of these cases we gain the ability to devote resources to a good opportunity that we could not previously have exploited.
The EA community has so far focussed on discovering and assessing existing funding opportunities, which is not surprising given its historical roots in charity evaluation. This is not an unreasonable strategy, even if the opportunities which you assess are simply generated randomly (as is the case in the DCP model).
But we might be able to do even better if we can generate high-quality opportunities deliberately, rather than having to wait for them to happen by accident. Matt Clifford, who runs EF, a London startup accelerator, describes traditional VC investing as waiting for high-value "lightning strikes", whereas an effective startup incubator should be like an electricity generator, producing value deliberately and predictably. I think we can aspire to something similar for high-impact organizations.
One way to try and create a high-impact organization is to sit down and think very hard about what organizations might be high-impact, and then once you think you have a good idea, go ahead and implement it. But we know that this is often a bad strategy! The modern startup industry functions more like an experimental laboratory. Sometimes you gain a great deal of information from actually trying things.7 Experimentation has the added virtue that a successful experiment can gradually transition into a exploitation opportunity as it grows.
There are a number of organizations in or around EA who are working on exploration through experimentation:
However, I think there is room to do much more, both directly and in capacity-building. For example:
- Charity Entrepreneurship found multiple promising ideas, but as far as I know nobody has picked up any of the remaining ones.
- Charity Entrepreneurship has primarily targeted health so far, but we should be doing similar explorations in other promising areas.
- The Good Technology Project is a "technique specialist" focussing on technology startups, analogously we could have e.g. an organization that focussed on starting policy campaigns targeting important problems.
- We could create other kinds of institution for systematically generating high-impact organizations, such as impact-focussed startup incubators.8 This is essentially capacity-building for exploration through experimentation - I am particularly excited by this idea.
- We could experiment with VC-style gated-funding models which encourage demonstrating results rapidly and aborting failed experiments.9
Conclusion
As a community, we should invest more in exploration.10 Concretely,
- Organizations doing research, like GiveWell and OPP, should invest even more in capacity-building.
- We should start and fund experimental new organizations.
- We should start and fund organizations that focus on systematically generating further high-impact organizations.
In particular, starting or funding new high-impact organizations does not seem to be a focus area for the "giga-funders" like OPP, so this may be a place where small donors can bet better.
Finally, we should start doing this as soon as possible. Exploration tends to take time, and there is already some possibility that OPP could saturate most of our best available opportunities. Time to expand the frontier!
[Cross-posted from my blog]
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If we consider value of information (VoI), then saying "we should do more exploration" just amounts to saying "the VoI of this (exploration) action is high enough to make it the best option", in which case we are only ever doing exploitation.
I could probably have written this post and only talked about VoI, and I don't think it would have changed the conclusions much. However, I find the exploration/exploitation dichotomy to be intuitive, so I've stuck with it.↩
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I still think this model is plausible for many meta-charities, especially since we think that many of them are drawing from fat-tailed distributions.↩
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Of course, this is not a problem if we are already planning to give later.↩
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Making some very rough estimates of the numbers of exploratory research staff employed by various organizations: I believe OPP has ~10, CEA has ~5, GiveWell has ~7, ACE has ~3, Sentience Politics ~3. I don't have a good idea how many researchers are employed by other relevant organizations across all cause areas, but I'm fairly sure the number of full-time researchers must be less than 100.↩
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There is also exploration work relevant to EA that is being done outside the movement, e.g. by J-PAL, but I'm disregarding that as we have less influence over how that money is spent.↩
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The few exceptions that I know of are the studies relating to the effectiveness of vegan outreach (e.g. this one), although those have had some problems.↩
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Obviously the best strategy is a mixed one - pure experimentation is very slow and wasteful. But if we're anything like other domains we should expect to have quite a lot of experimentation in the mix.↩
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This is similar to what Spark Wave is doing, but there's room for more work in this space!↩
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The Global Innovation Fund does something like this, with different funding levels for organizations at the "Pilot", "Test" and "Scale" phases.↩
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Note that this is a bit more specific than just saying "fund meta", since I'm not including things like EA movement-building which have historically been considered part of "meta". I think these are helpful, but not the best ways to improve exploration.↩
Good post!
Animal Charity Evaluators also has the Animal Advocacy Research Fund which has $1,000,000 to give out over 3 years to fund research, which you should probably count as money spent on exploration.
Depending on what you mean by 'direct work', x-risk orgs could also be counted as currently doing mostly exploration, or at least don't fit very neatly into the dichotomy. Still even with these additions I doubt this would raise it above ~$20 million a year, which would probably not be enough to change your conclusion.
I'm unsure where the balance should lie quantitatively. I think that $100 million would probably be too much, and $10 million is probably too low.
I agree that x-risk work doesn't fit nicely into this: it's not even clear whether you'd want to count the output of research as "actually" what you want or as VoI.